ECE Course Descriptions

ECE Course Descriptions

ECE 501B Advanced Linear Systems Theory (3)

Mathematical fundamentals for analysis of linear systems. Maps and operators in finite and infinite dimensional linear vector spaces, metric spaces, and inner-product spaces. Introduction to representation theory. Eigensystems. Spectral theorems and singular value decomposition. Continuity, convergence, and separability. Sturm-Louisville theory.
Prerequisite(s): Graduate Standing or Permission of the Instructor


ECE 503 – Probability and Random Processes for Engineering Applications (3)

Probability, random variables, stochastic processes, correlation functions and spectra with applications to communications, control, and computers.
Prerequisite(s): SIE230 or Equivalent


ECE 505 – Model-Integrated Computing

This course addresses modeling, metamodeling, advanced object-oriented system design, model-integrated computing, and integrated systems. Behavioral, structural, and process modeling are among the modeling approaches to be examined. Additional topics include semantic mapping, models of computation, graph rewriting, and domain-specific modeling. In lieu of a midterm and final exam, an individual project will be performed over the course of the semester, constituting a large portion of the grade.
Course Requisites: ECE 373. Graduate standing or consent of instructor. Recommend a strong command of C++ or Java programming language.


ECE 506 – Reconfigurable Computing (3)

In this class, we investigate the state-of-the-art in reconfigurable computing both from a hardware and software perspective; understand both how to architect reconfigurable systems and how to apply them to solving challenging computational problems. The purpose of this course is to prepare students for engaging in research on reconfigurable computing.
Course Requisites: Digital design fundamentals, computer architecture and organization, programming language (C is a must, VHDL/Verilog knowledge preferred).


ECE 509 – Cyber Security – Concept, Theory, Practice (3)

This course provides an introduction to technical aspects of cyber security. It describes threats and types of attacks against computers and networks to enable students to understand and analyze security requirements and define security policies. Security mechanisms and enforcement issues will be introduced. Students will be immersed in the cyber-security discipline through a combination of intense coursework, open-ended and real-world problems, and hands on experiments.
Course Requisites: ECE 578.


ECE 527 – Holography and Diffractive Optics (3)

This course describes the nature of holographic and lithographically formed diffraction gratings and the tools necessary for their design and analysis. Course topics include a description of the interference and Fourier relations that determine the amplitude of diffracted fields, analysis of volume gratings, properties of holographic recording materials, computer generated holograms, binary gratings, analysis of applications of holography including data storage, imaging systems, photovoltaic energy systems, polarization control elements, and associative memories. We will also have a number of lab demonstrations fabricating holograms in a new type of photopolymer.
Course Requisites: OPTI 502, OPTI 505R or ECE 459 or ECE 559.


ECE 529 – Digital Signal Processing (3)

Discrete-time signals and systems, z-transforms, discrete Fourier transform, fast Fourier transform, digital filter design. Graduate-level requirements include additional homework and a term project.
Prerequisite(s): ECE 340, MATH 322


ECE 535A – Digital Communications Systems I (3)

The purpose of the course is to give students a comprehensive introduction to digital communication principles. The major part of the course is devoted to studying how to translate information into a digital signal to be transmitted, and how to retrieve the information back from the received signal in the presence of noise and intersymbol interference (ISI). Various digital modulation schemes are discussed through the concept of signal space. Analytical and simulation models for digital modulation systems are designed and implemented in the presence of noise and ISI. Optimal receiver models for digital base-band and band-pass modulation schemes are covered in detail. Graduate work will include more challenging problem sets and exam problems, and a C/C++ simulation project.
Prerequisite(s): ECE340A


ECE 538 – Radar Signal Processing

Radar fundamentals: radar range equation, waveforms, ambiguity functions. Signal Processing: Pulse compression, synthetic aperture radar (SAR)inverse SAR, moving target indication (MTI), Pulse-Doppler radar, space time adaptive processing (STAP).


ECE 539A From Photonics Innovation to the Marketplace (3)

This course covers the process of technology development in the photonics industry, both from the perspective of formal processes and case studies. Key aspects of the commercialization process including intellectual property, new product development processes, technical marketing and team building are treated in an interactive program informed by the instructor’s 15 years of industry experience in both large corporate R&D organizations and entrepreneurial startups. Graduate-level requirements include completing an executive summary of their business plan/invention disclosure project that is a portion of the Group Gate 2 presentation grade.


ECE 542 – Digital Control Systems (3)

Modeling, analysis, and design of digital control systems; A/D and D/A conversions, Z-transforms, time and frequency domain representations, stability, microprocessor-based designs. Graduate-level requirements include additional homework and a term project.
Prerequisite(s): ECE 340


ECE 562 – Computer Architecture and Design (3)

This course aims to provide a strong foundation for students to understand modern computer system architecture and to apply these insights and principles to future computer designs. It provides basic knowledge, fundamental concepts, design techniques and trade-offs, machine structures, technology factors, software implications, and evaluation methods and tools required for understanding and designing modern computer architectures including multicores, embedded systems, and parallel systems. The course is structured around the three primary building blocks of general-purpose computing systems: processors, memories, and networks. The first part of the course focuses on the fundamentals of each building block. Topics include processor microcoding and pipelining; cache microarchitecture and optimization; and network topology, routing, and flow control. The second part goes into more advanced techniques and will enable students to understand how these three building blocks can be integrated to build a modern computing system. Topics include superscalar execution, branch prediction, out-of-order execution, register renaming and memory disambiguation; VLIW, vector, and multithreaded processors; memory protection, translation, and virtualization; and memory synchronization, consistency, and coherence. The third part addresses parallel computing, including multicore architectures, datacenters and cloud computing.d others. Graduate-level students will be required to complete a term paper and extra homework.
Prerequisite(s): ECE 175, ECE 274, ECE372 or consent of instructor


ECE 564 – Advanced Topics in Computer Networks (3)

Current state of the Internet; multimedia requirements; quality of service in IP networks; RSVP; real-time protocol (RTP); differentiated-services (Diffserv) architecture; traffic control; traffic policing and admission control; burstiness and traffic characterization; flow control; TCP enhancements; fairness and protection; packet scheduling and buffer management; inter-domain routing (BGP protocol); intra-domain routing (OSPF protocol); hierarchical routing; web caching; medium access control in wireless LANs; mobile ad hoc networking (routing and MAC protocols, power control, topology control); addressing schemes and MAC design for sensor networks; and others.


ECE 566 – Knowledge-System Engineering (3)

Offered every two years. Knowledge systems are intelligent systems that totally or partially involve computational representation and processing of knowledge. This class introduces the principles and techniques for engineering and developing of knowledge systems. Alternative computational structures for knowledge representation, procedures and algorithms for computational processing, automated reasoning and inference from knowledge, learning new knowledge, handling uncertainty in information, knowledge-based decision networks, Distributed knowledge systems, Alternative system architectures and engines. Graduate-level requirements include a more extensive and in-depth project, have to do additional assignment or question on the exam.


ECE 573 – Software Engineering Concepts (3)

In-depth consideration of each of the phases of the software project life code. Object-oriented design and programming. Includes a large-scale software development project involving groups of students. Graduate-level requirements include additional homework and a term project.


ECE 578 – Fundamentals of Computer Networks (3)

This course provides an introduction to the fundamental principles of computer networks and data communications. Emphasis is given on current technologies and architectures for establishing direct link and packet-switched networks, sharing access to a common communication medium, internetworking and routing, end-to-end flow control, congestion control and recourse allocation, and network security.
Prerequisite(s): ECE175 – Computer Programming for Engineering Applications (C programming)


ECE 579 – Principles of Artificial Intelligence (3)

Provides an introduction to problems and techniques of artificial intelligence (AI). Automated problem solving, methods and techniques; search and game strategies, knowledge representation using predicate logic; structured representations of knowledge; automatic theorem proving, system entity structures, frames and scripts; robotic planning; expert systems; implementing AI systems. Graduate-level requirements include additional assignments.
Prerequisite(s): ECE 373 or equivalent course.


ECE 639 – Detection and Estimation in Engineering Systems (3)

Communication, detection and estimation as statistical inference problems. Optimal detection in the presence of Gaussian noise. Extraction of signals in noise via MAP and MMSE techniques.
Course Requisites: ECE 503.


ECE 677 – Distributed Computing Systems

Design, architecture and programming of distributed computing systems. The course consists of three parts: 1) Networks and Protocols in high performance distributed systems; 2) Architectural issues of designing and implementing disturbed systems (distributed operating systems, distributed file systems, concurrency control and redundancy management, load balancing, and security); and 3) Distributed computing paradigms (shared memory, message passing, and web based computing, virtual computing, and Grid computing).


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