Cybersecurity and Cyber Systems Courses | 2024-2025 Graduate Catalog | SIU

Review of logical circuit design. Hardware description languages. Algorithms for high-speed addition, multiplication and division. Pipelined arithmetic. Implementation and control issues using PLA's and microprogramming control. Cache and main memory design. Input/Output. Introduction to interconnection networks and multiprocessor organization. Prerequisite: CS 320 with a grade of C or better or graduate standing.

Credit Hours: 3

This course is a comprehensive introduction to modern robotics with an emphasis on autonomous mobile robotics. Fundamentals of sensors and actuators as well as algorithms for top level control are discussed. Multi-robotics and human-robot interaction issues are explored. A group project is an integral part of this course. Prerequisite: CS 330 with a grade of C or better or graduate standing. CS fee: $125.

Credit Hours: 3

This course will be an introduction to the administration of Linux systems, with emphasis on security for networked systems. Topics to be covered include: installation and configuration of Linux distributions, typical maintenance activities, and security measures for networked systems. Students will have access to lab machines for hands on practice. Prerequisite: CS 306 with a grade of C or better or graduate standing.

Credit Hours: 3

This course builds on the knowledge gained in CS 306, to prepare students to do advanced development on Linux/UNIX platforms. The topics studied are critical for achieving high performance in large-scale, high-load networked software systems. These topics include development techniques such as profiling, concurrent programming and synchronization, network programming for high-load servers, advanced I/O alternatives, and IPC such as shared memory. The course will involve the study of code from Open Source projects like Apache and Nginx. The focus will be on the C language, but other languages will also be considered. Students must complete a significant network software project. Prerequisites: CS 306 and CS 335, with grades of C or better, or graduate standing with C language and Linux system programming experience.

Credit Hours: 3

This course is a comprehensive introduction to modern cryptography, with an emphasis on the application and implementation of various techniques for achieving message confidentiality, integrity, authentication and non-repudiation. Applications to Internet security and electronic commerce will be discussed. All background mathematics will be covered in the course. Prerequisite: CS 330 with a grade of C or better and MATH 221 or graduate standing.

Credit Hours: 3

This course will explore the various means that an intruder has available to gain access to computer resources. We will investigate weaknesses by discussing the theoretical background, and whenever possible, actually performing the attack. We will then discuss methods to prevent/reduce the vulnerabilities. This course is targeted specifically for Certified Ethical Hacking (CEH) exam candidates, matching the CEH exam objectives with the effective and popular Cert Guide method of study. Prerequisite: CS 202 with a grade of C or better or graduate standing.

Credit Hours: 3

A broad overview of the principles, mechanisms, and implementations of computer security. Topics include cryptography, access control, software security and malicious code, trusted systems, network security and electronic commerce, audit and monitoring, risk management and disaster recovery, military security and information warfare, physical security, privacy and copyrights, and legal issues. Prerequisite: CS 306 with a grade of C or better or graduate standing.

Credit Hours: 3

This course uses advanced features of the Java programming language to develop networked, distributed, and web-based applications. Topics covered include, but are not limited to, sockets, datagrams, the Java security model, threads, multi-tier architectures, Java RMI, Java database connectivity, and Java-based mobile agents. Prerequisite: CS 306 with a grade of C or better or graduate standing.

Credit Hours: 3

Cybersecurity has become a ubiquitous concern well beyond finding solutions to post-mortem threat analysis. The course provides a broad overview of security objectives and will cover fundamentals in confidentiality, integrity, and availability. Lectures will offer a broad range of topics on digital forensics. Students will be trained for an investigation mindset. Contemporary tools and techniques for digital forensics and investigations are reviewed. Security for stationary and mobile platforms are foci of current course in both forensic and active modes. There will be multiple hands-on homework and laboratories as well as a practical project as an integral part of this course. Prerequisite: CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

With the proliferation of wireless networks, security is at odds with privacy and integrity. The course provides a broad overview of security strategies for wireless networks. Topics will range from intrusion detection and network security protocols to collaborative computing. Contemporary tools and techniques for wireless network security are reviewed. A hands-on project will be an integral part of this course. Prerequisite: CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

Introduction to compiler construction. Design of a simple complete compiler, including lexical analysis, syntactical analysis, type checking, and code generation. Prerequisite: CS 306 and 311 each with a grade of C or better or graduate standing.

Credit Hours: 3

A top-down approach addressing the issues to be resolved in the design of distributed systems. Concepts and existing approaches are described using a variety of methods including case studies, abstract models, algorithms and implementation exercises. Prerequisite: CS 335 with a grade of C or better or graduate standing.

Credit Hours: 3

Cloud Computing (CC) represents a recent major strategic shift in computing and Information Technology. This course explores fundamental principles, foundational technologies, architecture, design, and business values of CC. Understanding will be reinforced through multiple angles including: analysis of real world case studies, hands-on projects and in-depth study of research developments. Prerequisites: CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

The course concentrates on the relational model, database design, and database programming. Topics include relational model, relational algebra, SQL, constraints and integrity, transaction support, concurrency control, database design, normalization, backup, recovery, and security. A comprehensive product-like project is an integral part of the course. Prerequisite: CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

The goal of this course is to introduce and develop an understanding of the computing and communication for Internet of Things as a subset of Cyber-Physical systems. Connectivity among devices in our daily lives such as WiFi-enabled thermostats, smart grids, and driverless cars is ushering in an era of sociality that transcends human social networks to machine to machine networks. Prerequisites: CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

An introduction to classical machine learning theory and practical techniques. Topics to be covered include computational learning theory (VC theory), linear classification and regression models, SVMs and kernel methods, decision trees, the bias-variance tradeoff, overfitting, and regularization. Prerequisites: CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

Principles, practices and methodology for development of large software systems. Object-oriented principles, design notations, design patterns and coping with changing requirements in the software process. Experiences with modern development tools and methodologies. A team project is an integral part of this course. Prerequisite: CS 330 with a grade of C or better or graduate standing; CS 306 with a grade of C or better recommended.

Credit Hours: 3

Search and heuristics, problem reduction. Predicate calculus, automated theorem proving. Knowledge representation. Applications of artificial intelligence. Parallel processing in artificial intelligence. Prerequisite: CS 311 and 330 each with a grade of C or better or graduate standing.

Credit Hours: 3

An introduction to the field of machine learning and soft computing. It covers rule-based expert systems, fuzzy expert systems, artificial neural networks, evolutionary computation, and hybrid systems. Students will develop rule-based expert systems, design a fuzzy system, explore artificial neural networks, and implement genetic algorithms. Prerequisite: CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

This course is an introductory course on bioinformatics algorithms and the computational ideas that have driven them. The course includes discussions of different techniques that can be used to solve a large number of practical problems in biology. Prerequisite: CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

Design and analysis of computer communication networks. Topics to be covered include queuing systems, data transmission, data link protocols, topological design, routing, flow control, security and privacy, and network performance evaluation. Prerequisite: CS 330 with a grade of C or better or graduate standing; CS 306 recommended.

Credit Hours: 3

Concepts of mobile and wireless systems are presented. These concepts include, but are not limited to, Routing and Medium Access for Mobile Ad hoc and Wireless Sensor Networks, Mobile IP, Wireless LAN and IEEE 802.11. Hands-on group lab experience is an integral component in the course. Prerequisite: CS 330 with a grade of C or better, or graduate standing or consent of the instructor.

Credit Hours: 3

(Same as MATH 447) Graph theory is an area of mathematics which is fundamental to future problems such as computer security, parallel processing, the structure of the World Wide Web, traffic flow and scheduling problems. It also plays an increasingly important role within computer science. Topics include: trees, coverings, planarity, colorability, digraphs, depth-first and breadth-first searches. Prerequisite: MATH 349 with C or better.

Credit Hours: 3

(Same as MATH 449) This course will introduce the student to various basic topics in combinatorics that are widely used throughout applicable mathematics. Possible topics include: elementary counting techniques, pigeonhole principle, multinomial principle, inclusion and exclusion, recurrence relations, generating functions, partitions, designs, graphs, finite geometry, codes and cryptography. Prerequisite: MATH 349 with C or better.

Credit Hours: 3

The fundamental concepts of the theory of computation including finite state acceptors, formal grammars, Turing machines, and recursive functions. The relationship between grammars and machines with emphasis on regular expressions and context-free languages. Prerequisite: CS 311 and 330 each with a grade of C or better or graduate standing.

Credit Hours: 3

An in-depth treatment of the design, analysis and complexity of algorithms with an emphasis on problem analysis and design techniques. Prerequisites: CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

(Same as MATH 471) Introduction to algorithms for finding extreme values of nonlinear multivariable functions with or without constraints. Topics include: convex sets and functions; the arithmetic-geometric mean inequality; Taylor's theorem for multivariable functions; positive definite, negative definite, and indefinite matrices; iterative methods for unconstrained optimization. Prerequisite: MATH 221 and MATH 250 with C or better.

Credit Hours: 3

(Same as MATH 472) Introduction to finding extreme values of linear functionals subject to linear constraints. Topics include: recognition, formulation, and solution of real problems via the simplex algorithm; development of the simplex algorithm; artificial variables; the dual problem and duality theorem; complementary slackness; sensitivity analysis; and selected applications of linear programming. Prerequisite: MATH 221 with C or better.

Credit Hours: 3

(Same as MATH 475) Introduction to theory & techniques for computation with digital computers. Topics include: solution of nonlinear equations; interpolation & approximation; solution of systems of linear equations; numerical integration. Students will use MATLAB to study the numerical performance of the algorithms introduced in the course. Prerequisites: MATH 221 and MATH 250 with C or better.

Credit Hours: 3

This course utilizes computational and graphical approaches to solve statistical problems. A comprehensive coverage on modern and classical methods of statistical computing will be given. Case studies in various disciplines such as science, engineering and education will be discussed. Various topics such as numerical integration and simulation, optimization and maximum likelihood estimation, density estimation and smoothing as well as re-sampling will be presented. Students will be able to create graphical and numerical display based on their data analysis results using R programming language. Prerequisite: MATH 250 and CS 306 or CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

Problems and processes in the design of highly usable systems. Understanding stakeholders, requirements, tasks, prototyping, evaluation, guidelines and design process and heuristics. Interactive software concepts and implementation considerations. A group project is an integral part of this course. Prerequisite: CS 306 with a grade of C or better or graduate standing.

Credit Hours: 3

Principles and techniques of computer graphics. Interactive graphics software development using a modern graphics standard. Topics include: primitives, transforms, clipping, modeling, viewing, rendering, texture, animation and ray tracing. A group project is an integral part of this course. Prerequisite: CS 306 with a grade of C or better or graduate standing; MATH 150 and 221 are recommended.

Credit Hours: 3

This course focuses on software implementation and development aspects of game production including: software process, system architecture, frameworks, entity management and interaction design, game design, production and business issues as well as technical foundations in graphics modeling and rendering, collision detection, physics, artificial intelligence, and multiplayer techniques. Prerequisite: CS 330 with a grade of C or better or graduate standing.

Credit Hours: 3

Selected advanced topics from the various fields of computer science.

Credit Hours: 1-6

Individual projects involving independent work. Special approval needed from the instructor.

Credit Hours: 1-6

Supervised study. Preparation and presentation of reports. Special approval needed from the instructor.

Credit Hours: 1-6

Hardware and software elements of multiprocessors, multicomputers, pipeline and array machines, data flow architecture and other state-of-the-art architectures. Design principles related to machine structures, interconnection networks, control software and hardware, data storage and access. Prerequisite: CS 401.

Credit Hours: 3

An introduction to different aspects of fault-tolerance in computing systems. Redundancy techniques with an emphasis on information redundancy, software fault-tolerance, coding techniques, algorithm-based fault-tolerance, fault-tolerant interconnection network architecture, DFT techniques, and quantitative evaluation methods. Prerequisite: CS 401.

Credit Hours: 3

Advanced security concepts of distributed systems and wireless networks are presented. Topics include IEEE 802.11 security, Wireless Encryption and Authentication, Key Management in Networks, Distributed Denial of Service Attacks, Routing Security, Intrusion Detection and Mobile Code Security. Prerequisite: CS 410 with a grade of C or better or consent of the instructor.

Credit Hours: 3

A survey of modeling techniques and Meta languages for the formal specification of the syntax and semantics of high-level programming languages. Prerequisite: CS 311.

Credit Hours: 3

An advanced level course on nonprocedural programming with emphasis on logic programming, pure functional programming, and the characteristics of the declarative style common to these two paradigms. Topics include logic programming, functional programming, implementation consideration for each along with current research topics in the areas. Prerequisite: CS 311.

Credit Hours: 3

Rigorous treatment of advanced topics in operating systems. Multiprocessors and distributed operating systems. Highly concurrent machines. Performance analysis of memory management and scheduling algorithms. Recovery techniques in distributed computation. Security in operating systems. Prerequisite: CS 335 with a grade of C or better.

Credit Hours: 3

This course introduces fundamentals of modern blockchain-based systems as well as cryptocurrency applications. Topics for discussion include consensus and distributed computing, smart contracts, privacy and secrecy, and other relevant computational platforms. Non-currency applications of blockchains, and legal and social implications will be outlined. Students will be required to develop a term project. Prerequisites: CS 330 with grade of C or better or CS 410 or graduate standing.

Credit Hours: 3

A continuation of 416 including advanced topics in lexical and syntax analysis, error recovery, sematic analysis, code optimization and compiler compilers. Prerequisite: CS 416.

Credit Hours: 3

An advanced treatment of parallel and distributed computing; review of hardware and software considerations for parallel computation; development and analysis of parallel algorithms (with particular attention to the communication and synchronization costs associated with parallel algorithms); effect of granularity on performance; a comparison of the parallel and distributed programming paradigms including a detailed study of the central features of each approach; software systems for distributed computing including exposure to one or more distributed programming environments; the direction of parallel computing as suggested by recent, high level parallel languages; parallelizing serial programs; parallelizing compilers; future directions of parallel and distributed computing systems. The course will include a student project. Prerequisite: CS 420.

Credit Hours: 3

This course offers a survey of security and privacy issues in Cloud Computing systems along with an overview of current best practices and available technologies. Threat model as well as practical applications of secure Cloud Computing are explored. Prerequisite: CS 410 or graduate standing.

Credit Hours: 3

This course combines essential ideas from linguistics and artificial intelligence to for machine understanding and generation of language. We will cover language syntax, semantics, and pragmatics and discuss the applications such as information extraction, question answering and dialog systems. Machine learning is the main computational tool to solve NLP problems and will devote a part of the course to discussing ML approaches that model NLP tasks. Deep Neural Networks and their ability in learning representations are also part of our approach to NLP problems. We will discuss learning representations and learn about transformer-based architectures that help in learning rich representations. This course is suitable for students who are willing and able to learn abstract concepts, complete programming assignments, develop a project, and produce a term paper. Prerequisite: CS 330 with a grade of C or better.

Credit Hours: 3

A detailed treatment of advanced topics in data base systems including, but not limited or restricted to, relational database theory, query optimization, recovery techniques, concurrency control, distributed database systems, security and integrity and database machines. Prerequisite: CS 430.

Credit Hours: 3

The course covers introductory topics in cyber-physical systems security. The goal is to expose students to fundamental security primitives specific to cyber-physical systems and to apply them to a broad range of current and future security challenges. Various tools and techniques used by hackers to compromise computer systems or otherwise interfere with normal operations are explored using tools that are unique to interacting with cyber-physical systems. Restricted to graduate standing or consent of the instructor.

Credit Hours: 3

A detailed study of two or three topics relevant to information systems. Topics may include but are not limited to sorting, searching, information retrieval and automatic text processing, database security and encryption, distributed databases and data communication. Prerequisite: CS 430. Special approval needed from the instructor.

Credit Hours: 3-6

This course provides a series of comprehensive and in-depth lectures on the core techniques in data mining and knowledge discovery; addresses the unique issues of big data; and discusses potential applications of data mining particularly on big data analysis. Major topics include: data preparation, association mining, classification (and prediction), clustering, characteristics and challenges of big data, and strategies of big data mining and analysis. Prerequisites: CS 330 and CS 430 with grades of C or better or consent of instructor.

Credit Hours: 3

This course provides comprehensive and in-depth discussions of big data management and analytics. Main subjects include computation and programming models, management and analytics algorithms, and platforms/frameworks especially designed for big data. The objective of this course is to equip students with the ability to understand, use, and build big data management and analytics systems or tools. Prerequisites: CS 430 with a grade of C or better or graduate standing.

Credit Hours: 3

The purpose of this course is for students to acquire in-depth knowledge of advanced aspects of machine learning. This course will cover topics including classification, clustering, the foundation of deep learning, convolutional Neural Networks, recurrent Neural Networks, and some other advanced topics-deep reinforcement learning and deep generative models. Students will learn the foundations of machine learning, deep learning, and develop skills for performing research to advance the state of knowledge in machine learning. Prerequisites: CS 434 or CS 437 with a grade of C or better. Concurrent enrollment in CS 434 or CS 437 is allowed.

Credit Hours: 3

Theorem proving, the Resolution Principle, strategies, and achievements. Program verification. Natural language processing. Other selected topics. Prerequisite: CS 436.

Credit Hours: 3

This course is designed to provide students with advanced topics in expert systems theory. Topics covered include: knowledge representation, methods of inference, reasoning under uncertainty, and inexact reasoning (fuzzy logic). A practical introduction to expert systems programming serves to reinforce and clarify the theoretical concepts. Prerequisite: CS 330 or consent of instructor.

Credit Hours: 3

Game theoretic concepts apply whenever actions of several players are interdependent. This course will provide an introduction to classic game theory and strategic thinking including dominance, Nash equilibrium, and stability. Social choice, social learning, and online mechanism design are then discussed. We will examine how game theoretic concepts can be used in developing reasoning strategies, i.e., algorithms. Application of game theoretic framework to telecommunication and human networks is an integral part of this course. Restricted to graduate standing or consent of instructor.

Credit Hours: 3

This is an advanced treatment of fundamental concepts in the design of intelligent autonomous agents and agent systems. Classic agent theories, architectures, algorithms, and languages are discussed. An agent-based project is an integral part of this course. Restricted to graduate standing or consent of instructor.

Credit Hours: 3

Topics include routing protocols used in internet; data compression techniques; telecommunication systems - its services, architecture and protocols; high speed networks; routing protocols in mobile ad-hoc networks; and a detailed performance analysis of different window flow control and congestion control mechanisms using queuing theory. Prerequisite: CS 440 with a grade of C or better, or consent of the instructor.

Credit Hours: 3

The Chomsky hierarchy of formal grammars and the corresponding classes of automata. Turing machines and basic concepts of computability. Recursive and recursively enumerable languages. Closure properties. Undecidable problems about Turing machines and context-free languages. Deterministic context-free languages and the construction of LR parsers. Prerequisite: CS 451.

Credit Hours: 3

Turing machines and other models of computation. Computable functions. Church's thesis. Solvable and unsolvable problems. Introduction to complexity theory including the classes P and NP. Polynomial time approximation algorithms for NP-complete problems. Prerequisite: CS 451.

Credit Hours: 3

(Same as MATH 572) Selected advanced topics in Numerical Analysis chosen from such areas as: approximation theory; spline theory; special functions; wavelets; numerical solution of initial value problems; numerical solution of boundary value problems; numerical linear algebra; numerical methods of optimization; and functional analytic methods. Special approval needed from the instructor.

Credit Hours: 1-12

Study of computer graphics for realistic image synthesis. Object modeling and associated date structures. Advanced rendering techniques such as raytracing and radiosity. Efficiency considerations. Image composition and compression. Current advances and research problems in realistic computer graphics. Prerequisite: CS 485.

Credit Hours: 3

An introduction to the area of pattern recognition and data science. This course will cover basic and advanced theories, algorithms, and practical solutions of statistical pattern recognition. It covers bayesian learning, parametric and non-parametric learning, data clustering, component analysis, boosting techniques, sequential data, reinforcement learning, and deep learning with neural networks.

Credit Hours: 3

Supervised readings in selected subjects. Graded S/U only. Special approval needed from the instructor.

Credit Hours: 1-6

Selected advanced topics from the various fields of computer science. Repeatable on different topics toward degree credit.

Credit Hours: 1-3

Preparation and presentation of reports. Graded S/U only. Special approval needed from the instructor.

Credit Hours: 1-4

A practical exercise in the design, implementation, documentation and deployment of a project. A project may be completed through internship, work/study, or a supervised project. For Ph.D. students only, an internship could include face-to-face or online teaching.

Credit Hours: 3-9

Special approval needed from the instructor.

Credit Hours: 3-9

Dissertation research. Hours and credit to be arranged by the student's academic advisor. Graded S/U only. Restricted to admission to Ph.D. in computer science program.

Credit Hours: 1-9

For those graduate students who have not finished their degree programs and who are in the process of working on their dissertation, thesis, or graduate project. The student must have completed a minimum of 24 hours of dissertation research, or the minimum thesis or graduate project hours before being eligible to register for this course. Concurrent enrollment in any other course is not permitted. Graded S/U or DEF only.

Credit Hours: 1

Principles of Model-Based Systems Engineering. Data modeling and rule modeling. Functional architecture. Behavioral models and executable models. Verification requirements. Requirements analysis. System test and evaluation. Process validation and verification. SysML graphical modeling language. Prerequisites: ECE 315 and ECE 327 with grade of C or better.

Credit Hours: 3

Introduction to hardware security. Hardware attacks. Trust and countermeasures on the electronic supply chain. Hardware IP piracy and reverse engineering. Attacks: Side channel, test-oriented, physical, PCB. Hardware security primitives. Hardware obfuscation. PCB authentication. Prerequisite: ECE 327 with a C or better.

Credit Hours: 3

Combinatorial aspects of system reliability. Parallel, standby, n-modular redundancy. Common cause failures. Information coding techniques. Reliability optimization and apportionment. Fault-tolerant computer design techniques. Prerequisites: ECE 315 and ECE 327 with grade of C or better.

Credit Hours: 3

Principles of performance evaluation, processor microarchitecture, instruction-level parallelism, static and dynamic pipeline considerations. Superscalar processors. Multiprocessor systems. Memory hierarchy design, cache design. Mutual exclusion and synchronization mechanisms. Prerequisite: ECE 329 with a grade of C or better.

Credit Hours: 3

Principles, design, and implementation of network systems security. Network security basics (computer networks and network security module), packet sniffing and spoofing, network security systems (firewall, virtual private network, and instruction detection systems), security tools (AES, Hash, RSA, and public key infrastructure), and advanced topics such as bitcoin and block chain. Prerequisite: ECE 315 with a grade of C or better.

Credit Hours: 3

Principles of computer systems security. Vulnerabilities, attacks and defenses, cryptographic primitives, authentication, digital signature, access control. Software systems security: buffer overflow, virus, SQL injection. Networking security: denial of service attack, firewall and IDS, Wi-fi security. Hardware systems security: secure processing and secure co-processor. Cloud, edge and IoT security. Prerequisite: ECE 315 with a C or better and consent of instructor.

Credit Hours: 3

R programming language: Vectors, Matrices, Lists, Data Frames, Factors, Tables. Review of machine learning techniques: Numerical Regression, Logistic Regression, k-Nearest Neighbors, Decision Trees. ROC curves. Various application case studies. Prerequisite: ECE 315 or equivalent with a grade of C or better.

Credit Hours: 3

Ray optics, wave optics, beam optics, polarization of light, Fourier optics, fiber optics, electro-optics, nonlinear optical media, acousto-optics, and photonic switching. Prerequisite: ECE 375 with a grade of C or better. Lab fee: $50 to help defray the cost of consumable items as well as maintaining or replacing the existing equipment.

Credit Hours: 4

The sources of electrical signals in biological systems. Methods and types of sensors for sensing bioelectrical signals, including amperometric, potentiometric, piezo-electric, impedance, and FET based biosensors. Interface between biosensors and electronics for sensor signal condition and data acquisition. Precision electronics for biosensor signal acquisition, including potentiostat, current, charge, capacitance and impedance sensing circuit, lock-in amplifier. Prerequisite: BME 337 or ECE 345 with a grade of C or better.

Credit Hours: 3

Fundamental theories of light, including the wave theory of light and the particle theory of light; Fundamental interactions between light and matter, including reflection, refraction, absorption, scattering, fluorescence, and polarization; Biology of cells and tissues; Tissue optical properties; Tissue-targeted contrast agents; Coherence and interference; Light transport in turbid media; Diagnostic applications of light, including microscopy, spectroscopy, fluorescence imaging, fluorescence-lifetime imaging, optical coherence tomography, diffuse optical tomography, and/or biosensors; Therapeutic applications of light, including photodynamic therapy, photothermal therapy, and/or laser ablation. Prerequisites: ECE 235, MATH 251, and PHYS 205B with a grade of C or better.

Credit Hours: 3

Fundamentals of semiconductor physics, including the use of doping and biasing to control electronic potentials in devices; Fundamentals of integrated circuits, including the design and fabrication of diodes, transistors, and interconnects; Fundamental interactions between light and matter, including reflection, refraction, and absorption; Structure and operating modes of photodiodes; Architectures and operating principles for charge coupled device (CCD) image sensors and complementary metal-oxide-semiconductor (CMOS) image sensors; Performance metrics for image sensors, including the noise floor, the full-well capacity, the quantum efficiency, and fixed pattern noise; Construction of color image sensors; Signal processing for image sensors, including color interpolation and color correction. Prerequisites: ECE 235, ECE 235L with a grade of C or better.

Credit Hours: 3

Introduction to micro-electro-mechanical systems (MEMS), manufacturing techniques, microsensors, microactuators, microelectronics and micro-controllers. Lecture and laboratory. Prerequisite: ECE 315 and ECE 356. Lab fee: $50 to defray cost of equipment and materials for the project(s).

Credit Hours: 3

This course introduces the students to the field of digital signal processing. The course topics include discrete-time signals and systems analysis, z-transform, discrete Fourier transform, fast Fourier transform algorithms, digital filter design, and other related topics. Prerequisite: ECE 355 with a grade of C or better, or consent of instructor. Lab fee: $20 to help defray cost of software licenses and equipment.

Credit Hours: 3

Basic machine learning concepts: Model selection, feature scaling, bias-variance trade-off, regularization, Performance metrics and validation techniques, Probability and statistics review. Supervised learning: Linear/non-linear regression and logistic regression, Generalized linear models, Generative learning models, Bayes decision theory, Naive Bayes classifier, Nearest neighbor classifiers, Hidden-Markov models, Support vector machines, Kernel methods, Bagging, Boosting. Unsupervised Learning: Clustering: K-means, Expectation-maximization, Anomaly detection, Dimensionality Reduction: Principal components analysis, transform techniques. Basics of reinforcement learning and deep learning. Restricted to Senior or graduate standing.

Credit Hours: 3

Anatomy and physiology of the cerebral cortex, Feed-forward Networks, Multilayer Perceptrons, Recurrent Networks, Hopfield Networks, Self-organizing Networks, Convolutional Neural Network, Applications to pattern recognition, robotics, image processing, and speech processing. Prerequisite: MATH 305 or ECE 315 or ECE 351 with a C or better or consent of instructor.

Credit Hours: 3

This course covers fundamentals of wireless communication systems. Topics include wireless system architectures, channel modeling, introduction to cellular systems, digital modulation and multiple-access techniques, introduction to multi-antenna techniques, performance analysis, wireless physical layer security, future trends in wireless communications. Prerequisites: ECE 315 and ECE 355 or consent of instructor. Project-based fee: $20 to help defray cost of software licenses.

Credit Hours: 3

Introduction to cyber systems in digital health, fundamentals of medical informatics, electronic health, biometric recognition and security, cybersecurity for medical devices and digital technology integration, cybersecurity for healthcare facilities, ethics and federal regulations. Prerequisite: MATH 251 or consent of instructor.

Credit Hours: 3

Transmission lines for communications. Guided wave principles and resonators. Applications in electronics, optoelectronics and photonics. Principles of radiation. Solution techniques for Laplace's equation and one-dimensional wave equation. Prerequisite: ECE 375.

Credit Hours: 3

History and future of energy resources and their use as a component of electrical systems. Fossil fuels and renewable energy sources. Environmental and economical impacts of various energy sources. Electric energy generating plants and distributed generation. Design of hybrid renewable energy systems. Prerequisite: ECE 385 with a grade of C or better.

Credit Hours: 3

Modeling and analysis of electric power systems. Topics covered: ac power, generators, power transformers, transmission line parameters and steady state operation, computation of power flows. The course uses power system analysis software. Lecture. Prerequisite: ECE 385 with a minimum grade of C.

Credit Hours: 3

Diagnostic ultrasound is an ultrasound-based biomedical imaging technique used to visualize muscles, tissue, and many internal organs, to capture their size, structure and any pathological lesions. This course is an introduction to the principles and applications of biomedical ultrasound. This course will focus on fundamentals of acoustic theory, principles of ultrasonic detection and imaging, design and use of currently available tools for performance evaluation of diagnostic devices, and biological effects of ultrasound. Prerequisite: MATH 305 and ECE 355 with a grade of C or consent of instructor. Restricted to enrollment in ECE programs. Lab fee: $30 to help defray cost of equipment, supplies, and software licenses.

Credit Hours: 3

Probability and basic number theory, block ciphers and key-recovery security, pseudorandom functions, symmetric encryption, hash functions, message authentication codes, authenticated encryption, asymmetric encryption, digital Signatures, key distribution, lattice-based cryptography, identity-based encryption, zero-knowledge e techniques, introduction to quantum cryptography.

Credit Hours: 3

Fundamentals and importance of the Internet of Things (IoT). Sensors and hardware components of IoT systems. Design of energy-efficient IoT systems from circuit to system level. Connectivity in IoT, off-loading strategies, and federated learning concepts. Applications of IoT in smart cities, healthcare, agriculture, and augmented/virtual Reality. Prerequisites: ECE 329 and ECE 321 (or equivalent) with a grade of C or better or consent of instructor.

Credit Hours: 3

Overview of the ordinary physiology of cells and tissues and the abnormal physiology associated with cancer and/or other major diseases. Role of surgeries in the practice of modern medicine with a special focus on cancer treatment and/or other important procedures. Environment of and people inside the operating room. Therapeutic and diagnostic tools and techniques available in the operating room. Open and minimally invasive surgeries. Introduction to image-guided surgeries. Imaging systems and contrast agents for image-guided surgeries. Introduction to robotic surgeries. Preclinical research, clinical research, and FDA-approval process. Prerequisite: ECE 355 (or equivalent).

Credit Hours: 3

Analysis of deep learning techniques such as deep feedforward networks, regularization, optimization algorithms, convolutional networks, and sequence modeling. Utilization of machine learning frameworks such as Tensorflow and Pytorch. Investigation of hardware architectures for machine learning applications such as GPUs, TPUs, and systolic arrays. Students will also work on a semester-based project utilizing the latest advancements in deep neural networks. Students that have completed ECE 411 are not eligible to enroll in ECE 511 as the courses cover similar topics to an extent.

Credit Hours: 3

Compared to infrastructure based wireless communication systems, ad hoc wireless networks present several unique advantages. Thus, it has been widely studied as an important wireless communication paradigm. This graduate level course first introduces several widely adopted wireless communication technologies and then presents the concept, structure, and principles of ad hoc wireless networks. The course also introduces the details of several popular ad hoc wireless networks including mobile ad hoc networks, delay tolerant networks, wireless sensor networks, and connected vehicle networks. Novel applications in those networks will also be introduced. The course work will include paper and literature review, presentations, assignments, and a project that will enable students to be familiar with ad hoc wireless networks. NS2 will be used for student project in this course. Students can gain experience on NS2. Students who have taken ECE 412 are ineligible to enroll. Project-based fee: $10 to help defray cost of equipment.

Credit Hours: 3

Principles of the design and layout of Very Large Scale Integrated (VLSI) circuits concentrating on the CMOS technology. MOS transistor theory and the CMOS technology. Characterization and performance estimation of CMOS gates, CMOS gate and circuit design. Layout and simulation using CAD tools. CMOS design of datapath subsystems. Design of finite state machines. Examples of CMOS system designs. Laboratory experience in CMOS VLSI design. Restricted to enrollment in ECE program. Students who have taken ECE 423 are ineligible to enroll. Project-based fee: $35 to help defray cost of software licenses and equipment.

Credit Hours: 3

Introduction of modern embedded system application, platform architecture and software development. Principles of embedded processor architecture, operating systems and networking connectivity. Design and optimize in terms of system power, security and performance. Lecture and laboratory. Students who have taken ECE 424 will not receive credit for this course. Prerequisites: Courses equivalent to ECE 296, ECE 296L, ECE 321, ECE 329, with grades of C or better or consent of instructor. Lab fee: $10 to help defray cost of equipment.

Credit Hours: 3

This course introduces the design of three dimensional VLSI integration systems, including through-silicon-via (TSV) process, characterization and modeling, 3D IC systems design, mixed signal simulation, data management, testing, process, variation, thermal and reliability challenges, as well as review of 3D system design examples. Laboratory experience in design tools (Cadence Virtuoso and Liberate, AMS simulator). Prerequisite: ECE 345 and ECE 423 with a grade of C or better. Restricted to enrollment in ECE program.

Credit Hours: 3

This course is dedicated for advanced Digital VLSI architecture and system implementation for high performance and low power digital signal processing applications. Application-specific processors and architectures to support real time processing of signal processing systems will be studied. Hands-on experience of using state-of-the-art CAD tools on designing such kind of VLSI architecture and systems. Upon completion of this course, students will entail large HDL-based implementation of a complete VLSI system. Students who have taken ECE 426 are ineligible to enroll. Prerequisite: ECE 327 with a grade of C or better. Project-based fee: $35 to help defray cost of software licenses and equipment.

Credit Hours: 3

Analysis of IoT architectures and core IoT modules, integration of sensors and data acquisition systems, power-aware optimizations, and embedded operating systems. Investigation of cloudlet topologies and services, edge to cloud protocols, and security. Special focus will be given on data analytics and machine learning in the cloud and the edge.

Credit Hours: 3

Cryptographic systems and hardware. Advances in physically unclonable functions. Random number generators. Watermarking. Hardware metering. Side channel attacks including fault injection and power analysis. Types of hardware Trojan attacks (forms and sizes). Detection of hardware Trojans. Hardware tampering and obfuscation. Countermeasures against hardware attacks and hardware authentication. Counterfeit circuits: detection and avoidance. Trust issues in FPGAs. JTAG security and trust. SoC security requirements and secure design. Prerequisite: ECE 418 or graduate standing.

Credit Hours: 3

Systems Security: Programming, Exploitation, Shellcode, Countermeasures. Network Security: Network Protocol Security, DDoS attack, Web Security and Intrusion Detection Systems. State-of-the-art research topics in computer security: Security and Privacy issues for IoT, human factors and economic and policy issues.

Credit Hours: 3

Principles of the automated synthesis, verification, testing and layout of Very Large Scale Integrated (VLSI) circuits concentrating on the CMOS technology. Resource allocation and scheduling in high-level synthesis. Automation of the logic synthesis for combinational and sequential logic. The physical design automation cycle and CMOS technology considerations. Fault modeling and testing. Timing analysis. Laboratory experience using commercial tools for synthesis and layout. Students who completed ECE 425 can't take ECE 520. They are similar. Prerequisite: ECE 327 with a C- or better or enrollment in ECE graduate programs. Project-based fee: $30 to help defray cost of software licenses and equipment.

Credit Hours: 3

Concepts of error detection, location and correction in digital systems. Codes for error detection and correction. Models and simulations of faults. Design of tests for combinatorial and sequential circuits. Testability. Design of digital systems with testability. Prerequisite: ECE 423, ECE 425 or consent of instructor. Restricted to enrollment in ECE program.

Credit Hours: 3

Theoretical and practical aspects of production testing of VLSI circuits. Relations between physical defects and fault models. Procedures for generating test inputs. Design modifications for test application and theory of built-in self-test. Prerequisite: ECE 425 or ECE 520 with a minimum grade of C or consent of instructor. Restricted to enrollment in ECE program. Project-based fee: $25 to help defray cost of software licenses.

Credit Hours: 3

Source of power dissipation, technology impact on power dissipation, low power circuit techniques, energy recovery, synthesis of low power circuits, low power components. Prerequisite: ECE 423 or ECE 513 with a minimum grade of C or consent of instructor. Restricted to enrollment in ECE program. Project-based fee: $35 to help defray cost of software licenses and equipment.

Credit Hours: 3

Binary decision diagrams, finite state machines and finite automata. Design automation concepts in logic level synthesis, optimization and verification for combinational as well as sequential logic. Technology mapping. Prerequisite: ECE 425 or ECE 520 with a minimum grade of C or consent of instructor. Restricted to enrollment in ECE program. Project-based fee: $35 to help defray cost of software licenses and equipment.

Credit Hours: 3

Advances in the automation of VLSI layouts with emphasis on recent developments in deep submicron, FPGA and MCM technologies. Floor planning, placement, routing objectives in high performance designs using deep submicron technology. Timing analysis in the presence of crosstalk. FPGA architectures and design with dynamically reconfigurable FPGAs. Physical design automation for MCMs. Prerequisite: ECE 425 or ECE 520 with a minimum grade of C or consent of instructor. Restricted to enrollment in ECE program. Project-based fee: $35 to help defray cost of software licenses and equipment.

Credit Hours: 3

Protocol processing, packet processing algorithms, classification and forwarding, queuing theory, switching fabrics, network processors, network systems design tradeoffs. Prerequisite: ECE 422 and ECE 429 or consent of the instructor. Restricted to enrollment in ECE program.

Credit Hours: 3

Importance of interconnection networks and networks-on-chip (NOCs). Specifications and constraints. Topology, routing, flow control, deadlock, livelock, arbitration, allocation, performance analysis, simulation. Restricted to enrollment in ECE program.

Credit Hours: 3

Principle and practice of designing and implementing Application-Specific Integrated Circuits (ASIC). Field Programmable Gate Arrays (FPGA). Timing analysis, timing closure and managing difference clock domains in ASIC design. Complex arithmetic circuits. Digital signal processing (DSP) circuits. FPGA microprocessors. Students who have taken ECE 428 are ineligible to enroll. Project-based fee: $50 to help defray cost of equipment and consumable items.

Credit Hours: 3

Principles of performance evaluation, processor microarchitecture, instruction-level parallelism, static and dynamic pipeline considerations. Superscalar processors. Multiprocessor systems. Memory hierarchy design, cache design. Mutual exclusion and synchronization mechanisms. Students who have taken ECE 429 are ineligible to enroll. Restricted to enrollment in ECE program.

Credit Hours: 3

(Same as ENGR 530) Theory of data acquisition and measurement systems. Criteria for selection of data acquisition hardware and software, instruments, sensors and other components of scientific and engineering experimentation. Methods for sampled data acquisition, signal conditioning, interpretation, analysis and error estimation. Restricted to enrollment in ECE program. Project-based fee: $60 to help defray cost of software licenses and equipment.

Credit Hours: 3

Analysis and design of mixed-signal integrated circuits. Digital to analog converter (DAC). Analog to digital converter (ADC). Sigma-delta data converters. Performance analysis of signal chains containing both analog and digital signal processing functions. Prerequisite: ECE 446 with a minimum grade of C. Restricted enrollment in ECE program. Project-based fee: $60 to help defray cost of software licenses and equipment.

Credit Hours: 3

Multi-core architecture, threads, thread execution models, thread priority and scheduling, concurrency, multi-threaded programming models, synchronization, performance measurement and local balance, software tools for multi-threaded programming. Restricted to ECE students or consent of advisor. Students who have taken ECE 432 are ineligible to enroll. Project-based fee: $20 to help defray cost of equipment.

Credit Hours: 3

(Same as BME 533) Fundamentals of speech production system, signal analysis of speech, speech coding, linear prediction analysis, speech synthesizing, and speech recognition algorithms. Students who have taken ECE 474 are ineligible to enroll. Prerequisite: MATH 250, ECE 355 with grades of C or better or consent of instructor.

Credit Hours: 3

(Same as BME 536) The nature of biomedical signals. Electricity in living tissue. Biomedical signal processing and modeling. Modeling and simulation of biomedical systems. Prerequisite: MATH 250, ECE 355 with a grade of C or better or consent of instructor. Project-based fee: $20 to help defray cost of software licenses.

Credit Hours: 3

Introduction of RF IC, passive RLC Networks, passive IC components, MOS Transistors, distributed systems, Smith Chart and S-Parameters, introduction to Band-width estimation, biasing and voltage reference, basic High Frequency Amplifiers, introduction to: noise in RF IC, Low Noise Amplifiers, Power Amplifiers, Phase-Locked Loops and Oscillators. Lecture and laboratory. Students who have taken ECE 440 are ineligible to enroll. Lab fee: $35 to defray the cost of software licenses and equipment.

Credit Hours: 3

Advanced software concepts and techniques to develop complex software projects on embedded systems. Concepts and techniques include system calls, structure of operating systems, advanced dynamic memory management, cross-compilation, scheduling techniques, and resource management. Students who have completed ECE 430 cannot take ECE 536. They are similar.

Credit Hours: 3

Fundamentals of electromagnetic theory, waveguides, photonic structures including photonic crystals and integrated micro-ring resonator, numerical simulations of photonic integrated circuits using the beam propagation method, finite-difference time-domain method, rate equations, and fabrication processes. Prerequisite: ECE 441 or consent of instructor. Restricted to enrollment in ECE program.

Credit Hours: 3

This course introduces the students to the field of medical instrumentation. Medical instrumentation is the application of advanced engineering technology to problems in biology and medicine. The course will focus on fundamentals of instrumentation systems, sensors, amplifiers, and signal precondition. In addition, the course also includes design and applications of medical instrumentation, biopotential measurement, biomedical signal processing, and other related topics. Students who have taken BME 438 or ECE 438 cannot receive credit for this course. Prerequisite: MATH 305 and ECE 355 or equivalent courses with a grade of C or better, or consent of instructor. Restricted to enrollment in ECBE programs. Project-based fee: $45 to help defray cost of software licenses and equipment.

Credit Hours: 3

Diagnostic ultrasound is an ultrasound-based medical imaging technique used to visualize muscles, tissue, and many internal organs, to capture their size, structure and any pathological lesions. This course is an introduction to the principles and applications of biomedical ultrasound. This course will focus on fundamentals of acoustic theory, principles of ultrasonic detection and imaging, design and use of currently available tools for performance evaluation of diagnostic devices, and biological effects of ultrasound. Students who have taken BME 439 or ECE 494 cannot receive credit for this course. Prerequisite: MATH 305 and ECE 355 or equivalent courses with a grade of C or consent of instructor. Restricted to enrollment in ECBE programs. Project-based fee: $30 to help defray cost of software licenses and equipment.

Credit Hours: 3

High frequency amplifier design techniques, noise in RF IC and CMOS low noise amplifiers (LNA), mixers, oscillators, PLLs, frequency synthesizers, power amplifiers, an overview of wireless architectures. Prerequisite: ECE 440 or ECE 535 or equivalent. Lab fee: $50 to defray the cost of software licenses and equipment.

Credit Hours: 3

Fundamentals of information theory: uncertainty and information, thermodynamics of information. Quantum information processing: essential quantum mechanics of states, measurements and Bell's theorem, operations, and their representations as matrices; quantum Shannon theory (von Neumann entropy); quantum entanglement. Quantum cryptography. Various quantum algorithms and computational complexity. Building blocks: qubits and qubit operations, quantum machines. Decoherence, quantum error correction, and fault tolerance. Physical realization and quantum devices: double quantum dot charge qubit, Rabi oscillations of an excitonic qubit, Quantum dot spin-qubits, Photonic quantum computing, Superconducting qubits. Prerequisite: Familiarity with electronic and photonic devices, information theory, theoretical computer science, or quantum mechanics will be beneficial.

Credit Hours: 3

Ray optics, wave optics, beam optics, polarization of light, Fourier optics, fiber optics, electro-optics, nonlinear optical media, acousto-optics, and photonic switching. Students who have completed ECE 441 cannot receive credit for this course. Prerequisite: ECE 375 (or equivalent) with a grade of C or better or consent of instructor. Project-based fee: $50 to help defray the cost of equipment and consumables.

Credit Hours: 3

Analysis and design of CMOS analog integrated circuits. Circuit noise analysis. Low-voltage high-performance operational amplifiers. Voltage and current reference circuits. Integrated analog filter circuits. Micropower circuits. Prerequisite: ECE 446 or ECE 546 with a minimum grade of C or consent of instructor. Restricted to enrollment in ECE program. Project-based fee: $35 to help defray cost of software licenses and equipment.

Credit Hours: 3

Geometrical optics, including refraction and reflection; Physical optics, including interference, diffraction, and polarization; Optical aberrations, including causes and effects; Fourier optics, with applications to imaging; Light sources, including LEDs and lasers; Photodetectors, including photodiodes and image sensors; Lens systems; Microscopes. Students who are taking or have taken ECE 448 are ineligible to enroll. Lab fee: $125 to defray cost of software license.

Credit Hours: 3

Technology drivers: Moore, More-Moore, and More-than-Moore trends. Case Study: Integrated health monitoring systems, 3-D SoCs. Review of Solid-State Theory: electronic, magnetic, optical and thermal properties of semiconductors. Energy Related Devices: solid-state lighting, solar cells, thermoelectric devices, piezoelectric devices, energy storages and supercapacitors. Optoelectronic and Photonic Devices: Imagers, LEDs, OLEDs, Lasers, LCDs, thin-film transistors (TFTs). Sensors and Detectors. Microwave and Terahertz Devices. Prerequisite: ECE 447 or ECE 423 or ECE 446 or PHYS 425 or PHYS 430 or instructor consent.

Credit Hours: 3

VLSI manufacturing: oxidation, photolithography, etching, doping; process integration and monitoring; Yield modeling. Design for manufacturability (DFM): Sources and impact of variability; Lithography aware design; Stress and related variations in FinFETs and beyond; Design solutions for analog systems, parametric fluctuations in digital systems, interconnects, compensation and limiting the degrees of freedom; Criticality-aware DFM. Process control: patterns, multivariate and supervisory control; Statistical experimental design; Process modeling and equipment diagnosis. Prerequisite: familiarity with physics of semiconductor devices (e.g., ECE 447 or ECE 423 or PHYS 425 with a grade of C or better, or instructor consent).

Credit Hours: 3

Analysis and design of electronic circuits, both discrete and integrated. Computer-aided circuit design and analysis. Design of amplifier and filter circuits. Circuit stability analysis and frequency compensation techniques. Restricted to enrollment in ECE program. Students who have taken ECE 446 are ineligible to enroll. Project-based fee: $10 to help defray cost of equipment.

Credit Hours: 3

Semiconductor industry and Moore's law. Review of quantum mechanics of atoms. From atoms to crystals: energy bands, effective mass and density-of-states. Semiconductor statistics. Carrier transport phenomena. PN junctions. Schottky junctions. Bipolar junction transistors (BJTs). MOSFETs: capacitance-voltage and current-voltage characteristics, threshold voltage, scaling and short-channel effects, SPICE models. CMOS process integration. Basic optoelectronic devices: LEDs and solar cells. Lecture and laboratory. Students who have taken ECE 447 are ineligible to enroll. Prerequisite: ECE 345 or equivalent. Project-based fee: $25 to help defray cost of software licenses.

Credit Hours: 3

Introduction: Classical Phenomena and Devices. Why Quantum Devices? Current Picture: Academia and Industry. Essential Statistical Mechanics. Essential Quantum Mechanics. Quantum Theory of Electrons: Quantization, Tunneling, Quantum Interference, Quantum Hall Effect, Scattering and Broadening, Dephasing and Shot Noise. Coulomb Blockade. Quantum Optics. Collective Phenomena and Spin. Relativistic Quantum Phenomena. Quantum Phase Transition. Quantum Computation. Prerequisite: ECE 447 or ECE 423 or ECE 446 or PHYS 425 or PHYS 430 with C or better or instructor consent.

Credit Hours: 3

Fundamentals of step index and graded index fiber waveguides using geometrical optics and Maxwell's equations. Other topics include design criteria, practical coupling techniques, discussion of optical sources and detectors used in light-wave communications, system examples, characterization and measurement techniques. Prerequisite: ECE 447 or ECE 448 or consent of instructor. Restricted to enrollment in ECE program.

Credit Hours: 3

Review of fundamental principles of semiconductor devices. NanoTransistor: Charge-based devices-MOSFETs, non-ideal, atomistic, and quantum effects in nanoscale MOSFETs, charge-coupled devices. Advanced MOSFETs: FinFETs, SOI, SiGe and III-Vs, carbon nanotubes, graphene and 2-D semiconductors, nanowires. High electron mobility transistors (HEMTs), HBTs, and power MOSFETs. Compact and SPICE models for MOS devices. VLSI interconnects, parasitic elements, 3-D integration and reliability issues. Non-charge based devices-tunnel FETs, spin-based devices. NanoMemory: EEPROM and Flash, phase change memory, memristors, magnetic and ferroelectric, spin-torque devices, DRAM and ZRAM cells. TCAD simulation of semiconductor devices. Prerequisite: ECE 447 or ECE 423 or ECE 446 or PHYS 425 or PHYS 430 with a C or better or instructor consent. Project-based fee: $25 to help defray cost of software licenses.

Credit Hours: 3

Axioms of probability, random variables and vectors, joint distributions, correlation, conditional statistics, sequences of random variables, stochastic convergence, central limit theorem, stochastic processes, stationarity, ergodicity, spectral analysis, and Markov processes. Restricted to graduate student status. Students who have taken BME 351 or ECE 351 cannot receive credit for this course. Restricted to enrollment in ECBE. Project-based fee: $20 to help defray cost of software licenses.

Credit Hours: 3

Estimation theory: parameter estimation, minimum variance unbiased estimators, sufficient statistics, Cramer-Rao lower bound, best linear unbiased estimators, maximum likelihood estimators, least squares, Bayesian estimation, maximum a posteriori estimators, minimum mean square error estimators, linear minimum mean square error estimators, Wiener filtering. Detection theory: hypothesis testing, likelihood ratios, Neyman-Pearson detection, Bayesian hypothesis testing, matched filtering, multiple hypothesis testing, sequential detection, composite hypothesis testing, uniformly most powerful tests, generalized likelihood-ratio tests. Prerequisite: ECE 551 or consent of instructor. Restricted to enrollment in ECE program.

Credit Hours: 3

Principles of Computer Networks. Protocols and system level implementations. Socket programming, router and switching fabric architecture, security and packet classification techniques, multimedia networking and QoS. Restricted to enrollment in ECE program. Students who have taken ECE 422 are ineligible to enroll. Project-based fee: $10 to help defray cost of equipment.

Credit Hours: 3

Statistical models for broadband wireless channels: angular, delay, Doppler and spatial domain characterizations, near/far-field propagation characteristics, spatial non-stationary propagation, and spatial wide-band fading. Broadband channel estimation, hybrid beamforming/detection and massive multi-antenna (MIMO) techniques. Millimeter-wave, terahertz, and holographic communication models. Reconfigurable/reflective intelligent surfaces and performance analysis. Broadband modulation multiple access techniques: index modulation, orthogonal time frequency space modulation, and orthogonal/non-orthogonal multiple access techniques. Prerequisites: ECE 315 and ECE 355 or consent of instructor. Restricted to EE or CEGR majors or consent of instructor.

Credit Hours: 3

Entropy and Mutual Information. Channel Capacity. Gaussian Channel. Linear Block Codes. Convolutional Codes. Advance Channel Coding Techniques. Students who have taken ECE 476 are ineligible to enroll. Restricted to enrollment in ECE program.

Credit Hours: 3

Digital communication signals and systems characterization. Deterministic receiver design. Probabilistic receiver design. Error control coding. Communication over band limited channels. Prerequisite: ECE 551 or consent of the instructor. Restricted to enrollment in ECE program.

Credit Hours: 3

Elements of computational science/engineering. High-performance clusters and software tools for HPCs. Essential numerical methods. Review of solid-state theory. Fundamental physics of charge transport in semiconductor VLSI devices. Numerical solution of Poisson's and carrier continuity equations in semiconductor devices. Boltzmann transport equation and Monte Carlo solutions. Electronic bandstructure calculations using the tight-banding formalism. Introduction to NEGF formalism. Commercial and non-commercial semiconductor device modeling tools. Prerequisite: Familiarity with physics of semiconductor devices (e.g., ECE 447 or ECE 423 or PHYS 425 with a grade of C or better, or instructor consent). Project-based fee: $25 to help defray cost of software licenses.

Credit Hours: 3

Basic concepts, scope and examples of digital image processing, digital image fundamentals, image sampling and quantization, an image model, relationship between pixels, enhancement in the spatial domain, enhancement in the frequency domain, image segmentation, basics of color image processing. Students who have taken ECE 458 are ineligible to enroll. Special approval needed from the instructor. Restricted to enrollment in ECE program.

Credit Hours: 3

A graduate level course on the theory and practice of Reinforcement Learning. The course covers topics such as finite and infinite horizon Markov decision processes, multi-armed bandit problem, dynamic programming, approximate dynamic programming, value and policy iteration, Q-learning, Monte Carlo methods, and stochastic approximation. Prior knowledge of machine learning and optimal control is helpful but not required.

Credit Hours: 3

Introduction to semiconductors. Materials for modern VLSI: crystals, tubular and monolayer materials, organic materials, heterostructures, wafers and notations. VLSI unit processes, contacts and interconnects, integration and packaging. Spontaneous formation and ordering of nanostructures. VLSI device characterization: wafer mapping, line width and contact resistance, measurement of MOS parameters, defect characterization using DLTS, carrier mobility and lifetime measurements. Optical characterization, electron beam microscopy, particle and X-ray techniques. Reliability and lifetime measurements: failure statistics and modes, hot carriers, NBTI, oxide integrity, electromigration and electrostatic discharge. Power dissipation and cooling. Prerequisite: Familiarity with physics of semiconductor devices (e.g., ECE 447 or ECE 423 or PHYS 425 with a grade of C or better, or instructor consent).

Credit Hours: 3

Components of mechatronics systems, mathematical modeling, system identification, numerical tools for design and analysis, single-loop controller design, embedded systems, data acquisition and signal conditioning, sensors, actuators, networked control. This course includes lab session. Students who have taken ECE 456 are ineligible to enroll. Lab fee: $35 to help defray the cost of software licenses.

Credit Hours: 3

Electromagnetic theory, analysis, design, fabrication, measurement and CAD applied to passive networks at microwave frequencies. Topics include: Transmission lines, Waveguides, Impedance matching, Tuning, Resonators, Scattering parameters, the Smith Chart. Lecture and Laboratory. Students who have taken ECE 479 are ineligible to enroll. Prerequisite: ECE 375 or equivalent. Restricted to enrollment in ECE program. Project-based fee: $100 to help defray cost of software licenses.

Credit Hours: 3

Pixel- and system-level design of charge coupled device (CCD) and complementary metal-oxide-semiconductor (CMOS) image sensors; Image processing pipelines for CCD and/or CMOS image sensors; Sources of nonlinearity and non-uniformity in image sensors, including photodiodes and amplifiers; Sources of noise in image sensors, including photon shot noise, dark shot noise, reset (kTC) noise, flicker (1/f) noise, and quantization noise; Materials used in image sensors, including silicon and indium gallium arsenide; Sources of resolution loss in image sensors, including crosstalk; Methods for evaluating image sensors; Technologies and techniques for moving beyond intensity-based imaging, including spectral imaging, polarization imaging, volumetric imaging, temporal imaging, and/or light-field imaging. Prerequisite: BME 453 or ECE 453 with a grade of C or better, or consent of instructor.

Credit Hours: 3

Optimization techniques for linear and nonlinear systems. Variational calculus. Dynamic programming. Pontryagin's maximum principle. Hamilton-Jacobi theory. Linear regulator. Bang Bang control, minimum time control, singular control. Discrete variational calculus. Combined estimation and control. Computational methods in optimal control. Prerequisite: ECE 456 or consent of instructor. Restricted to enrollment in ECE program.

Credit Hours: 3

Analysis and design of nonlinear dynamical systems. Topics include: nonlinear differential equations, stability, Lyapunov stability analysis, stability of perturbed systems, linearization, and central manifold theorem. Stabilization, feedback linearization, and controller design methods such as backstepping and sliding mode control.

Credit Hours: 3

Introduction to the structure and analysis of linear dynamical systems in time domain. Linear algebra review, solutions of linear differential equations, state-space representations, state transition matrix, and time varying systems. Introduction to fundamental mathematics of linear spaces and linear operator theory. Structural properties of linear systems such as controllability, observability, and stability. Design and synthesis of controllers and state observers for linear systems. Linear quadratic regulatory theory and Kalman filter.

Credit Hours: 3

Diagnostic x-ray projection imaging. Tomographic imaging. Ultrasound imaging and therapy. Magnetic resonance imaging (MRI). Signal and noise characteristics. Image quality evaluation. Three-dimensional image reconstruction algorithms. Students who have taken BME 432 cannot receive credit for this course. Prerequisite: MATH 305 and ECE 355 with a grade of C- or better, or consent of instructor. Restricted to enrollment in ECE program. Project-based fee: $30 to help defray cost of software licenses and equipment.

Credit Hours: 3

Basic machine learning concepts: Model selection, feature scaling, bias-variance trade-off, regularization, Performance metrics and validation techniques, Probability and statistics review. Supervised learning: Linear/non-linear regression and logistic regression, Generalized linear models, Generative learning models, Bayes decision theory, Naive Bayes classifier, Nearest neighbor classifiers, Hidden-Markov models, Support vector machines, Kernel methods, Bagging, Boosting. Unsupervised Learning: Clustering: K-means, Expectation-maximization, Anomaly detection, Dimensionality Reduction: Principal components analysis, transform techniques. Basics of reinforcement learning and deep learning. Restricted to Senior or graduate standing. Students who have taken ECE 469 cannot receive credit for this course. They are similar.

Credit Hours: 3

(Same as BME 538) Basic concept of Medical instrumentation, basic sensors and principles, amplifiers, biopotential electrodes, blood pressure and sound, measurement of respiratory system, chemical biosensors, Cellular measurements, Nervous system measurements, magnetic resonance imaging. Prerequisites: PHSL 410A or CHEM 444 or consent of instructor. Restricted to enrollment in ECE program. Lab fee: $45 to help defray cost of software licenses and equipment.

Credit Hours: 3

This course covers principles of communication systems. Topics include representation of signals and systems, amplitude modulation, angle modulation, probability theory and random processes for communication system designs, transition from analog to digital and pulse code/delta modulation, baseband digital transmission, digital band-pass transmission techniques, introduction to information theory and coding, wireless channel modeling, cellular systems and performance analysis. Lectures and laboratory projects. Prerequisites: ECE 315 and ECE 355 or consent of instructor. Students having passed ECE 478 are not eligible to enroll.

Credit Hours: 3

This course covers advanced topics in wireless communications. Topics include wireless system architectures, wireless channel modeling, cellular systems and co-channel interference, advanced digital modulation and multiple-access techniques, massive MIMO, mm-wave communications, performance analysis, radio resource allocation and optimization, wireless physical layer security, enabling technologies for 5G. Restricted to enrollment in ECE program or consent of instructor. Project-based fee: $20 to help defray cost of software licenses.

Credit Hours: 3

Anatomy and physiology of the cerebral cortex, Feed-forward Networks, Linear Associator, Multilayer Perceptrons, Feedback Networks, Hopfield Networks, ART. Applications to pattern recognition, robotics, image processing, and speech processing. Optical and electronic implementations. Students who have taken BME 470 or ECE 470 cannot receive credit for this course. Prerequisite: MATH 305 with a C or better or consent of instructor. Restricted to enrollment in ECE program.

Credit Hours: 3

Time-harmonic electromagnetic fields in dielectric and lossy media, transmission lines, antennas and resonators. Techniques include duality, image theory, reciprocity and integral equations. Boundary value problems solved for several frequently encountered symmetries. Prerequisite: ECE 477. Restricted to enrollment in ECE program.

Credit Hours: 3

Coupled-mode-analysis applied to nonlinear wave interactions, harmonic generation, parametric amplification, backward wave amplifiers, backward oscillation in laser systems, phase conjugation and multiple-wave mixing systems, Pockel and Kerr effects, and electro-optical modulations in optical communication systems. Prerequisite: ECE 375 or consent of instructor. Restricted to enrollment in ECE program.

Credit Hours: 3

Analysis, design, fabrication, measurement and CAD applied to basic antenna types. Fundamental parameters. Friis transmission equation. Impedance and pattern measurements. Resonant microstrip and wire antennas. Arrays and line sources. Lecture and laboratory. Students who have taken ECE 472 are ineligible to enroll. Prerequisite: ECE 375 or equivalent. Restricted to enrollment in ECE program. Project-based fee: $120 to help defray cost of software licenses.

Credit Hours: 3

Numerical solution of electromagnetic problems by methods that include finite element, integral equation, moment, spectral domain and finite difference. Examination of electromagnetic problems and their solutions in current literature. Prerequisite: ECE 573. Restricted to enrollment in ECE program.

Credit Hours: 3

Analysis, design and CAD of antennas. Numerical methods. Broadband, traveling-wave, frequency independent, electrically-small, aperture and microstrip antenna types. Prerequisite: ECE 472. Restricted to enrollment in ECE program.

Credit Hours: 3

Full-color image processing, image noise and degradation models, image restoration, inverse filtering, Wiener filtering, geometric transformations, image compression models, error-free compression, lossy compression, compression standards, dilation and erosion, opening and closing operations, morphological filtering, boundary descriptors, regional descriptors, principal components, vision-based pattern recognition. Prerequisite: ECE 558. Restricted to enrollment in ECE program.

Credit Hours: 3

Analysis and design of passive and active devices at microwave frequencies. Topics include: power dividers, couplers, filters, ferrite devices, noise, noise effects in detectors, mixers, modulators, amplifier and oscillator design, and an introduction to microwave systems. Prerequisite: ECE 479. Restricted to enrollment in ECE program.

Credit Hours: 3

THz band. Interaction of THz with matter, THz system components. Generation and detection of THz signals: photoconductive antenna, optical rectification, electro-optical sampling, quasi-phase-matching crystals, photo-mixers. Terahertz quantum cascade lasers: intersubband transitions, quantum dots photodetector, thermal detectors, device design and modeling. THz in 2D materials: Graphene and TMDs. Terahertz optics: metamaterials, photonic crystals, plasmonics. THz imaging: tomography, medical diagnostics. Spectroscopy: atoms, molecules, nanostructures. Nondestructive evaluation and security checks. THz wireless systems and THz in space. Prerequisite: familiarity with physics of semiconductor devices (e.g., ECE 447 or ECE 423 or PHYS 425 with a grade of C or better, or instructor consent).

Credit Hours: 3

Study and formal presentation by students of selected research in electrical and computer engineering. Restricted to students in the graduate program in Electrical and Computer Engineering. Special approval needed from the instructor.

Credit Hours: 1

The course introduces students to wind and solar energy power systems. Planning of wind generation; and operation of wind generators, mechanical and electrical design, power conditioning, control and protection. Planning, operation and design of electric solar plants; power conditioning, control and protection. Students who have taken ECE 481 are ineligible to enroll.

Credit Hours: 3

This course covers all the steps required for designing an actual power converter or electric drive system. The power stage design considerations, gate drive circuits, isolated high voltage/current measuring circuits, and application of a Texas Instrument Digital Signal Processor (DSP) for implementing different control schemes are discussed in detail. A brief introduction about the digital control theory and implementation of digital controller transfer functions using the DSP are provided as well. Students who have taken ECE 482 are ineligible to enroll. Project-based fee: $65 to help defray cost of software licenses and equipment.

Credit Hours: 3

Course content is roughly 1/3 power electronics, 1/3 applied control and 1/3 electric machinery and focuses on analysis, simulation, and control design of electric drive based speed, torque, and position control systems. Advanced topics depending on the semester are taught. Students who have taken ECE 483 are ineligible to enroll. Project-based fee: $65 to help defray cost of software licenses and equipment.

Credit Hours: 3

This course covers an entire range of topics related to analysis, design, control, and optimization of electric, hybrid, and plug-in hybrid power trains including automotive applications of adjustable speed motor drives, energy storage systems, and advanced power converters. Students who have taken ECE 484 are ineligible to enroll. Restricted to enrollment in ECE program or consent of the instructor. Lab fee: $65 to help defray cost of software licenses and equipment.

Credit Hours: 3

Fundamentals of power system stability, synchronous machine modeling and simulation, transient and small signal stability, control and protection, power system stabilizers, voltage stability, voltage collapse, concepts and devices of flexible ac transmission, mid-term and long-term stability.

Credit Hours: 3

The course covers advanced methods for the computation and analysis of power systems. Topics: circuit graph theory and network matrices, computation of electromagnetic transients, computation of power flows and faults, computation of system stability, stochastic methods in power systems, load forecasting, state estimation, unit dispatch. The course uses power system software. Lecture. Restricted to enrollment in the ECE program.

Credit Hours: 3

This course provides students with a comprehensive picture of the techniques used in modern power systems operation. The course introduces central "terminal" characteristics for thermal and hydroelectric power generation systems, along with new optimization techniques for tackling "real-world" power systems operating problems. The topics include: analysis of different bidding strategies in competitive electricity markets, prediction of load and price, analysis of power systems security, different methods of optimal power flow, analysis of power systems uncertainty and reliability, economic dispatch, and unit commitment analysis. Project-based fee: $65 to help defray cost of software licenses and equipment.

Credit Hours: 3

The course covers topics involving the design and operation of a power system. Topics: symmetrical and unsymmetrical power system faults, power system protection design, transient stability of power generators, power system economic operation, power system control, transient operation of transmission lines. The course uses power system software. Lecture. Students who have taken ECE 488 are ineligible to enroll.

Credit Hours: 3

Design of primary and secondary distribution networks. Load characteristics. Voltage regulation. Metering techniques and systems. Protection of distribution systems. Special topics related to power distribution. Students who have taken ECE 489 are ineligible to enroll. Prerequisite: ECE 235.

Credit Hours: 3

Individual advanced projects and problems selected by student or instructor. Restricted to graduate standing. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

Lectures on advanced topics of special interest to students in various areas of Electrical & Computer Engineering. This course is designed to offer and test new experimental courses in ECE. Restricted to enrollment in ECE program. Special approval needed from the instructor.

Credit Hours: 1-3

This course prepares graduate engineering students to communicate technical information to various audiences and for various purposes. Principles and strategies are applied to theses, dissertations, scholarly presentations, and other engineering documents such as lab reports, user manuals, business correspondences, job application materials, and engineering ethics. Research tools and software programs prepare students to deliver oral presentations on current engineering topics. Restricted to graduate standing. Does not count toward the hours required for graduation in the ECE program. Restricted to enrollment in ECE program.

Credit Hours: 3

(Same as BME 596) Principles of biomechanics, biomaterials, electrophysiology, modeling, instrumentation, biosignal processing, medical imaging, and biomedical optics. Professional moral and ethical issues in biomedical research and development. Students who have taken ECE 460 are ineligible to enroll. Prerequisite: MATH 250 with a grade of C or better or consent of instructor.

Credit Hours: 3

Credit Hours: 1-6

Dissertation research. Hours and credit to be arranged by director of graduate studies. Graded S/U only. Restricted to Admission to PhD program in Electrical and Computer Engineering.

Credit Hours: 1-16

For those graduate students who have not finished their degree programs and who are in the process of working on their dissertation, thesis, or research paper. The student must have completed a minimum of 24 hours of dissertation research, or the minimum thesis, or research hours before being eligible to register for this course. Concurrent enrollment in any other course is not permitted. Graded S/U or DEF only.

Credit Hours: 1