Courses

This is one of two lecture-lab courses of a 2-semester sequence for FRI students in Image and Acoustic Signals Analysis. Computing skills in MATLAB and Unix and introduction to computer programming. Technical writing using LaTeX. Students will learn research techniques while gaining understanding of research problems in this area. Prerequisites: HARP 170 and enrollment in Freshman Research Immersion (FRI) program. Offered in the Spring semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

An introduction to linear algebra for engineers with computer analysis, visualization, and mathematical programming. Linear algebra topics include matrix operations, systems of linear equations, determinants, solution to matrix equations, vector space, eigenvalues and eigenvectors. Introduction to engineering programming includes variables and arrays, matrix operation, functions, data representation, user defined functions and a brief introduction on graphical programming. Engineering applications such as the matrix representation of graphs, matrices applied to electric circuits and linear systems will be introduced during the class. Laboratory exercises. Prerequisite: Calculus I. Offered every spring semester. 4 credits. Levels: Undergraduate

This is the second of two lecture-lab courses of a 2-semester sequence for FRI students in Image and Acoustic Signals Analysis. Computer programming in C, and selected topics in multimedia signal processing and computer vision. Students will learn research techniques while gaining understanding of research problems in this area. Prerequisites: HARP 170 and EECE 115/CS 115, and enrollment in Freshman Research Immersion (FRI) program. Offered in the Fall semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

Fundamental and advanced concepts of digital logic. Boolean algebra and functions. Design and implementation of combinational and sequential logic, minimization techniques, number representation, and basic binary arithmetic. Logic families and digital integrated circuits and use of CAD tools for logic design. Laboratory exercises. Offered every fall semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

Units and definitions. Ohm's Law and Kirchhoff's Laws. Analysis of resistive circuits. Circuit analysis using: Nodal and mesh methods, Norton and Thevenin theorems, and voltage divider. Transient and sinusoidal steady-state response of circuits containing resistors, capacitors, and inductors. Laboratory exercises. Prerequisite: PHYS 132. Offered every spring semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

Overview of the fields of electrical engineering and computer engineering. Various sub-fields within EE and CoE are explored, with emphasis on how they are interrelated. Issues relevant to careers in EE and CoE (e.g., typical tasks done by EEs and CoEs) are explored. Offered every fall semester. 1 credit. Levels: Undergraduate

Design-based introduction to embedded computer systems. Organization and composition of computer processors, memory, and peripherals. Introduction to assembly-language and embedded C programming. Design of hardware and software for embedded processor applications. Laboratory exercises and design projects. Prerequisites: CS 211 and EECE 251. Offered every spring semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

Provides an introduction to continuous-time and discrete-time signals and linear systems. Topics covered include time-domain descriptions (differential and difference equations, convolution) and frequency-domain descriptions (Fourier series and transforms, transfer function, frequency response, Z transforms and Laplace transforms). Prerequisites: EECE 212 and 260 and MATH 324. Offered every fall semester. 4 credits. Levels: Undergraduate

Introduction to electronics, concentrating on the fundamental devices (diode, transistor, operational amplifier, logic gate) and their basic applications; modeling techniques; elementary circuit design based on devices. Laboratory exercises. Prerequisites: EECE 260 and EECE 251. Offered every fall semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

Physics and applications of electromagnetic fields as encapsulated in the vector form of Maxwell's equations. Static electrical and magnetic fields, time-varying electromagnetic fields, Poisson's equations, fundamental laws of electromagnetic fields (including Gauss's law, Ampere's law, Faraday's law, and Biot-Savart's law), time-harmonic fields, wave propagation, and transmission lines. Numerical techniques. Prerequisites: EECE 260 and MATH 323. Offered every spring semester. 4 credits. Levels: Undergraduate

Basic theory of semiconductors, p-n junctions, bipolar junction transistors, junction and MOS field effect devices; device design and modeling; and fabrication. Prerequisite: PHYS 132. Corequisite: EECE 315. Offered every fall semester. 3 credits. Levels: Undergraduate

Synchronous sequential circuit design. Algorithmic state machine method; state reduction; control-datapath circuit partitioning. Design of sequential arithmetic circuits. Memory interfacing; bus-based design. Specification and synthesis of digital systems using hardware description language and implementation using programmable logic devices. Simulation, analysis, testing and verification of digital systems. Laboratory exercises. Prerequisite: EECE 251. Offered every fall semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

Theoretical basis for and practical foundations of modern data communications within and between computing systems. Topics include: properties of signals and transmission media; data encoding and modulation, multiplexing, and multiple access; data integrity, error detection and error control, forward error correction; protocol concepts and design, flow control, sliding window protocols, data link control; local area networking, LAN standards, and interconnecting LANs; networking and inter-networking devices, bridges, repeaters, routers; inter-networking protocols. Lab exercises. Prerequisites: EECE 301 and EECE 351. Offered every spring semester. 4 credits. Levels: Undergraduate

"Introduction to analysis, design and modeling of control systems. Fourier and Laplace transforms, frequency response, transfer functions static and transient analysis. Systems block diagrams and signal-flow graphs. Concepts of stability. Numerical simulation and design of simple control systems. Introduction of discrete-time control. Prerequisite: EECE 301. Offered every spring semester. 3 credits. Levels: Graduate, Undergraduate

Fundamentals of communications systems. Modulation and demodulation methods. Characteristics of modern analog and digital communications methods. Prerequisites: EECE 301 and ISE 261. Offered every spring semester. 3 credits. Levels: Graduate, Undergraduate

Provides an overview of the professional aspects of the fields of electrical engineering and computer engineering. Topics to be covered include: typical career paths in EECE, engineering ethics, resume writing and job search techniques, preparing for graduate school, professional engineer license, etc. Offered every fall semester. 1 credit. Levels: Undergraduate

This course provides experience with the engineering design process, which spans significant areas of electrical and computer engineering. Lecture will focus on various aspects of the design process as well as discussions of component characteristics. EE student prerequisites: EECE 301 and EECE 315. CoE student prerequisites: EECE 315 and EECE 351. Offered every spring semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. . Levels: Undergraduate

Covers the general area of discrete-time signals and the analysis and design of discrete time systems. Topics include time domain analysis, solutions of difference equations, Z-transform analysis, sampling of continuous-time signals, discrete Fourier transforms, Fast Fourier Transforms, and spectral analysis. Processing of discrete-time signals using the DFT and FFT. Design and implementation of discrete-time filters. Extensive use of software simulations in a high-level language such as Matlab. Technical elective. Prerequisite: EECE 301. Offered every fall semester. 3 credits. Levels: Undergraduate

This course covers the fundamentals of digital audio signal processing. Topics include analog-to-digital converters and digital-to-analog converters, models for characterizing and analyzing quantization errors in digital audio, sampling rate conversion, design of filters and equalizers, algorithms for simulating room acoustics, and algorithms for implementing digital audio effects. Implementation of algorithms using Matlab is emphasized. 3 credits Prerequisites: EECE 301 and ISE 261, or instructor approval. Levels: Undergraduate

Introduction to codes and ciphers, information security, and mathematical basis of encryption. Cryptanalysis (code-breaking), modern block and stream ciphers, public-key cryptography, protocols, security engineering and threat management. Technical elective. Prerequisite: ISE 261 or MATH 327 and CS 211. Offered every fall semester. 3 credits. Levels: Undergraduate

This course will introduce the basics of quantum computing, including the theoretical physics background, mechanics of creation and manipulation of physical qubits, the mathematical basis for qubit gates, and quantum computing and algorithms. Credits 3 Prerequisites: EECE 212 and/or permission from instructor Offered Spring 2023 Levels: Graduate, Undergraduate

This course explores and analyzes the individual elements required to design a software-defined radio (SDR) receiver. Optimizations and tradeoffs are discussed as the receiver elements are integrated together. For the final project, the functional elements are integrated into a digital receiver system and the performance of the receiver is assessed. Topics include: modulation and demodulation, signal sampling, pulse shaping, bandwidth and data rate, synchronization, linear equalization, coding and decoding, timing recovery, and carrier recovery. Matlab is used to model the receiver elements and to implement the final project. Technical elective. Prerequisites: EECE 359 or EECE 377 or Equivalent. Offered every spring semester. 3 credits. Levels: Undergraduate

Introduction to analog circuit design. Course topics include large and small-signal analysis, circuit characteristics (gain, input/output resistance, etc.), amplifier structures, frequency/time response, feedback and stability, multistage amplifier and active filters. This course includes several assignments requiring the use of software tools for circuit simulation. Technical elective. Prerequisite: EECE 315. Offered every fall semester. 3 credits. Levels: Undergraduate

The purpose of this course is to form a solid basis for analyzing power systems. The course gives an overview of a power system and is focused on the basic concepts and elements that are essential in power system planning, operation and control. The course introduces modeling methods for major components in a power system and the methods for solving power flow problems. Specifically, the course addresses the following topics: an overview of power system and structure of electric power industry; the 3 phase circuits in power systems; steady state modeling of generators and transformers; transmission line modeling; power flow analysis. Technical elective. Prerequisites: EECE 323, or approval of instructor. Offered every fall semester. 3 credits. Levels: Undergraduate

Electronic processing of electrical energy. Overview of power electronics devices such as DMOSFET, IGBT and Thyristor. Power supply circuits from AC or DC sources as used in computers, inverters and variable-speed motor drives. Analytical and numerical techniques for simulation. Technical elective. Prerequisites: EECE 315 and EECE 301. Offered every fall semester. 3 credits. Levels: Undergraduate

Fundamentals of electric drive systems with applications emphasis. The course offers an integrative treatment of multiple components that make up electric drives, including electrical machines, power-electronics-based converters, mechanical systems, feedback controller design, and the interaction of the drives with the utility grid. Technical elective. Prerequisites: EECE 301 and EECE 323. Offered every spring semester. 3 credits. Levels: Undergraduate

The purpose of this course is to help students develop skills for analyzing electric power systems beyond power flow solutions. The following topics are covered: basics of economic dispatch; basics of fault analysis and fault current calculations; generator transients induced by grid faults; basics of power system protection; basics of stability concepts and stability analysis; basics of load frequency control, automatic generation control, reactive power and voltage control. Technical elective. Prerequisites: EECE 418. Offered every spring semester. 3 credits. Levels: Undergraduate

Provide a broad introduction to machine learning and its applications. We will briefly review python programming, statistics, and linear algebra. Then, fundamentals of machine learning will be introduced, with topics including supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks), unsupervised learning (clustering, dimensionality reduction, recommender systems), and fundamental theories (bias/variance theory). ECE applications such as time sequence forecasting, speech recognition, and image processing will be described. Offered Spring 2023 3 credits. Prerequisites: ISE 261 & MATH 324, permission from instructor Levels: Graduate, Undergraduate

Multidisciplinary Introduction to Microfabrication: Introduction to clean room tools, procedures, and theory through the fabrication and characterization of various devices from the fields of electrical engineering, mechanical engineering, physics and chemistry. Fabrication of the devices will cover most clean room tools and techniques, including lithography-based patterning methodologies; chemical vapor deposition; sputtering; thermal and e-beam evaporation; thermal oxidation; reactive ion etching; ion implantation; and wet chemical processing. The accompanying lecture will cover the theory of the tools used. Technical elective. Prerequisite: EECE 332 or an equivalent course in basic semiconductor device physics. Offered every spring semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

This course focuses on the science and engineering fundamentals of photovoltaic solar energy devices and systems. The lectures cover solar radiation, semiconductor properties, p-n junction theory, solar cell operating principles, solar cell device designs and fabrication of traditional crystalline silicon and thin film solar cells. Students will learn the advanced concepts for high efficiency solar cells and emerging photovoltaic devices like organic (plastic) solar cells and quantum solar cells. The course covers solar module interconnections, engineering design of solar electricity systems, and power conditioning at the systems level. Technical elective. Prerequisites: EECE 332 or equivalent is desirable but not essential. Offered every spring semester. 3 credits. Levels: Undergraduate

Physics, device structure, and operation of semiconductor lasers. Band structure in solids, optical processes in semiconductors, p-n junctions, and quasi-Fermi levels; rate equation model for semiconductor lasers, static and dynamic characteristics; characteristics of distributed feedback, Bragg reflector, vertical cavity and Fabry-Perot lasers. Technical Elective. Prerequisite: EECE 332. Offered every third semester. 3 credits. Levels: Undergraduate

This course introduces fundamentals of human organ-on-a-chip systems which refer to biomedical MEMS (bioMEMS) devices containing miniaturized human organs for drug screening, disease modeling and regenerative medicine. Topics to be covered in this course will focus on applications of electrical engineering principles combined with human cell culture techniques for the design, fabrication and interrogation of organ chip models of brain, lung, intestine and eye. The aims of the course include to: (i) study microfabrication and MEMS technologies in the context of human organ-on-a-chip implement and innovations; (ii) provide general background for in vitro cell culture techniques; (iii) review electrical, optical, biological sensor techniques for the analysis of organ-on-a-chip systems; and (iv) study the exemplary applications of organ-on-a-chip technology in biomedical research and medicine. This course also provides broad discussion on recent and future trends in human organ-on-a-chip systems and bioMEMS technologies. Prerequisites: EECE 332 or permission from instructor. Credits: 3 Levels: Undergraduate

This course will provide an overview of the components of system-on-a-chip (SOC) design from initial technology and architectural choices, to hardware/software design techniques (e.g., data/control flow modeling and implementation, embedded cores and coprocessors, hardware/software communication) as well as SOC implementation issues (e.g., performance, core selection, on-chip communication networks, power management, package constraints and cost). Also covered are SOC design and implementation processes (e.g., functional integration, simulation, clocking strategies, timing, design for test, and debug strategies). Technical elective. Prerequisites: EECE 287 and EECE 315. Offered every spring semester. 3 credits. Levels: Undergraduate

VLSI design, synthesis and test using hardware description language (HDL) at the register-transfer level (RTL). HDL programming and simulation basics, followed by advanced HDL programming for synthesis and test benching. Principles of RTL synthesis introduced. Design and synthesis of digital systems to meet constraints. Pre-synthesis and post-synthesis verification using simulation. Commercial synthesis tool discussed in detail. Technical elective. Prerequisite: EECE 351. Offered every fall semester. 3 credits. Levels: Undergraduate

This course will cover several topics in the area of computer architecture. We will discuss various concepts behind the designs of current microprocessors. In particular, the topics that will be covered in the course are: RISC machines and instruction set architectures, performance evaluation, pipelined architecture, static and dynamic scheduling, instruction-level parallelism, advanced pipelining, speculative execution, memory hierarchy and organization, multi-processing, compiler techniques (and more). Technical elective. Prerequisites: EECE 351 or equivalent. Offered every fall semester. 3 credits. Levels: Undergraduate

This is an introduction level computer network architecture course for senior/graduate students. The goal is to provide the students with a comprehensive picture of the technologies behind the Internet and applications on top of it. Starting with a brief review of some basics of networking, we will discuss from the lowest levels of packet transmissions through the highest levels of application software, under the umbrella of the TCP/IP architecture. Emphasis will be given on network architecture, components and design issues. Technical elective. Prerequisite: Basic knowledge of probability and statistics. Offered every fall semester. 3 credits. Levels: Undergraduate

The topics include the principles of MOSFET transistors, characteristics of CMOS digital circuits, layout design and process, performance analysis of CMOS gates, circuit design styles using MOSFET, performance, area and power optimization of CMOS circuits. Commercial design and simulation tools will be used in the class. Laboratory assignments include design, layout, extraction and simulation. Technical elective. Prerequisite: EECE 351. Offered every fall semester. 3 credits. Levels: Undergraduate

Introduction to security engineering, systemic analysis and common design principles. Cryptographic protocols, multilevel security, system evaluation, real-world vulnerabilities and attacks. Technical elective. Prerequisites: EECE 287 or CS 211, familiarity with C or C++ or similar programming language. Offered every spring semester. 3 credits. Levels: Undergraduate

Microcontroller based embedded systems design and analysis. Bare metal assembly and C software development for hardware and software integration. Driver based hardware abstraction and input/output synchronization. Sensor hardware integration, information extraction and fusion. Microcontroller applications and project. Technical elective. Prerequisites: EECE 251, EECE 315, and CS 211 or equivalent. Offered every fall semester. 3 credits. Levels: Undergraduate

State-space and frequency-domain methods for analysis and design of linear multivariable control systems. Digital implementation of controllers. Numerical simulation for performance evaluation of sampled-data control systems. Applications to embedded systems. Technical elective. Prerequisite: EECE 361 or equivalent. Offered every fall semester. 3 credits. Levels: Undergraduate

Electro-optic devices and systems. Blackbody, LED and laser sources, photodetectors, modulators, fiber optics, Fourier optics. Design of electro-optic systems. Technical elective. Prerequisite: EECE 323. Offered every other fall semester. 3 credits. Levels: Undergraduate

Fundamentals of digital communication systems; baseband modulation and demodulation; digital passband modulation and demodulation; channel coding, error detection; spread spectrum; signal space representation; bit error rate. Technical elective. Prerequisite: EECE 377 or equivalent. Offered every fall semester. 3 credits. Levels: Undergraduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Undergraduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Undergraduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Undergraduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Undergraduate

Faculty Advisor sections for ECE Senior Project I. Register after being assigned your project. Co-requisite: EECE 487 . Offered every fall semester. 1 credit. Levels: Undergraduate

Design projects in cooperation with local industry, other external clients, and university sponsored projects - outlining specifications, proposals, time schedules, and paper designs. Periodic design reviews with client, written and oral progress reports, final presentation. Evaluation based on individual and team performance. Prerequisites: EECE 387 and senior standing. Co-requisite: After being assigned your project, register for your Faculty Advisor's lab section of EECE 486. Offered every fall semester. 2 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

Continuation of team development project using lightweight version of industrial approach. Covers hardware and software builds, integration and test, and project completion; scope, cost, and time. Individual assignments; team written and oral progress reports, periodic reviews, integration and test plans, system verification methods, project reports, and project presentations. Evaluation based primarily on team performance. Prerequisites: EECE 487 and senior standing. Co-requisite: Register for your Project Advisor's lab section of EECE 489. Offered every spring semester. 2 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

Faculty Advisor sections for ECE Senior Project II. Evaluation based primarily on individual performance. Register for your Project Advisor's lab section. Co-requisite: EECE 488. Offered every spring semester. 1 credit. Levels: Undergraduate

Assist with undergraduate instruction of a formal course under the direct supervision of the course instructor. May count for one professional elective but may not be used to satisfy a technical elective unless significant work is done and always at the discretion of the Chair or Undergraduate Program Director. Taken with normal (letter) grade option ONLY; NOT P/F or S/U. Prerequisite: permission of course instructor. Offered every semester. Variable credit. Levels: Undergraduate

Engineering work experience in industry. Daily log book, memo progress reports and formal final report required. May satisfy, at most, one professional elective. Internships require course registration during the same term or semester as the internship is being completed (e.g., internships completed during the summer months would require summer registration). Taken with normal (letter) grade option ONLY; NOT P/F or S/U. Prerequisite: permission of faculty sponsor for internship. Offered every semester. Variable credit. Levels: Undergraduate

Individual study under direct supervision of a faculty member. Approval of proposed subject by the faculty member and plan of study must be obtained prior to registration. Can be used to satisfy either a technical or professional elective. If used to satisfy a technical or professional elective, it must be taken with normal (letter) grade option ONLY; NOT P/F or S/U. Offered every semester. Variable credit. Levels: Graduate, Undergraduate

Assist with faculty research. Approval of proposed subject by the faculty member and plan of research must be obtained prior to registration. Can be used to satisfy either a technical or professional elective. If used to satisfy a technical elective or professional elective, it must be taken with normal (letter) grade option ONLY: NOT P/F or S/U. Offered every semester. Variable credit. Levels: Undergraduate

Introduction to analog circuit design. Course topics include large and small-signal analysis, circuit characteristics (gain, input/output resistance, etc.), amplifier structures, frequency/time response, feedback and stability, multistage amplifiers and active filters. This course includes several assignments requiring the use of software tools for circuit simulation and a design project. Lecture portion meets with EECE 416. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 315. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

The purpose of this course is to form a solid basis for analyzing power systems. The course gives an overview of a power system and is focused on the basic concepts and elements that are essential in power system planning, operation and control. The course introduces modeling methods for major components in a power system and the methods for solving power flow problems. Specifically, the course addresses the following topics: an overview of power system and structure of electric power industry; the 3 phase circuits in power systems; steady state modeling of generators and transformers; transmission line modeling; power flow analysis. Lecture portion meets with EECE 418. Extra assignments, and/or final project will be required at the graduate level. Prerequisites: EECE 323, or approval of instructor. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

Fundamentals of electric drive systems with applications emphasis. The course offers an integrative treatment of multiple components that make up electric drives, including electrical machines, power-electronics-based converters, mechanical systems, feedback controller design, and the interaction of the drives with the utility grid. Lecture portion meets with EECE 421. Extra assignments, and/or final project will be required at the graduate level. Prerequisites: EECE 260, EECE 301 and EECE 323. Offered every spring semester. 3 credits. Levels: Graduate, Undergraduate

Electronic processing of electrical energy. Overview of power electronics devices such as DMOSFET, IGBT and Thyristor. Power supply circuits from AC or DC sources as used in computers, inverters and variable-speed motor drives. Analytical and numerical techniques for simulation. Lecture portion meets with EECE 419. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 315 and 301. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

This course is meant to provide an overview of the field of bioMEMS and bioelectronics. It will familiarize students with micro/nanofabrication techniques, Lab-on-a-chip, microfluidics, various microfluidic components, biofuel cells, drug delivery, neural interface, microsystems for cellular studies and tissue engineering. The objective of this course is to link engineering principles to biology, medicine, health, or bioenergy. Prerequisites: EECE 332. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

Selected topics in the advanced engineering mathematics, with special focus on their electrical engineering applications. Topics include ordinary and partial differential equations, Laplace transform, Fourier transform, linear algebra, matrix theory, numerical methods, complex analysis, optimization, probability and statistics. Prerequisites: calculus and differential equations. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

This course provides fundamental computer engineering knowledge for the design and analysis of digital systems. Includes applications of Discrete Math; Groups; Group Codes; Semi-groups; Synthesis of Networks; Reliable Design and Fault Diagnosis; Graphs; and Finite State Machines. Prerequisites: EECE 351 or equivalent and MATH 314 or equivalent. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

This course focuses on the science and engineering fundamentals of photovoltaic solar energy devices and systems. The lectures will cover solar radiation, semiconductor properties, p-n junction theory, solar cell operating principles, solar cell device designs and fabrication of traditional crystalline silicon and thin film solar cells. Students will learn the advanced concepts for high efficiency solar cells and emerging photovoltaic devices like organic (plastic) solar cells and quantum solar cells. The course covers solar module interconnections, engineering design of solar electricity systems and power conditioning at systems level. Lecture portion meets with EECE 432. Extra assignments, and/or final project will be required at the graduate level. Prerequisites: EECE 332 or equivalent is desirable but not essential. Offered every spring semester. 3 credits. Levels: Graduate, Undergraduate

The purpose of this course is to help students develop skills for analyzing electric power systems beyond power flow solutions. The following topics are covered: basics of economic dispatch; basics of fault analysis and fault current calculations; generator transients induced by grid faults; basics of power system protection; basics of stability concepts and stability analysis; basics of load frequency control, automatic generation control, reactive power and voltage control. Lecture portion meets with EECE 423. Extra assignments, and/or final project will be required at the graduate level. Prerequisites: EECE 502 or approval of instructor. Offered every spring semester. 3 credits. Levels: Graduate, Undergraduate

State-space and frequency-domain methods for analysis and design of linear multivariable control systems. Digital implementation of controllers. Numerical simulation for performance evaluation of sampled-data control systems. Applications to embedded systems. Lecture portion meets with EECE 462. Extra assignments, and/or final project will be required at the graduate level. Prerequisites: EECE 361 or equivalent. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

The purpose of this course is to introduce and study a number of engineering and economic problems in planning, operating and controlling power generation and transmission systems in electric utilities. The course will also introduce some mathematical optimization methods and apply them to solve power system problems. Specifically, the course will address the following topics: Power generation characteristics; Economic dispatch; Optimization with constraints; Unit commitment; Generation with limited energy supply; Transmission system effects; Power system security; Optimal power flow; Introduction of state estimation. The course targets graduate students with power/energy concentration. Prerequisites: EECE 418 or 502 or approval of instructor. Offered every other spring semester. 3 credits. Levels: Graduate, Undergraduate

Working principles and modeling of distribution grids, renewable energy resources, grid-tie battery system, microgrid, as well as analysis of integrated renewable energy systems. Prerequisites: EECE 418 and EECE 361, or equivalent, or approval of instructor. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

This module deals extensively with the design of high frequency high efficiency power electronic converters for AC-DC, DC-DC, and DC-AC, using pulse width modulation (PWM) and resonant energy conversion techniques. This module will make the student aware of the fundamental considerations needed to design power electronic converters in an industrial environment and conforming to different industrial standards especially in terms of electromagnetic interference (EMI)/Efficiency/Line harmonics (AC-DC). Prerequisites: EECE 419 and EECE 506, or EECE 507 or equivalent. Offered in the Fall. 3 Credits Levels: Graduate, Undergraduate

: Introduction to various electrical energy storage technologies focusing on supercapacitor and battery. Electrical design of storage systems and performance analysis. Electric energy storage application in photovoltaic and wind power based renewable energy systems. Modeling of electric energy storage in power and electronic systems such as in power conversion, electric drives, low power embedded systems and electrical traction. Broad impact of this course will be in understanding efficient and effective use of electrical energy in electronic, renewable energy and power conversion systems through supercapacitor array and battery based electric energy storage. 3 credits. Prerequisite: EECE315 (Electronics I), or equivalents, or approval of Instructor Levels: Graduate, Undergraduate

This course provides an overview of the field of renewable energy and fuel, made available from biologically derived materials with focus on its system implementations. In particular, the course will focus on innovative systems for bioelectricity, biofuel, biorefinery, and environmental applications. The objective of this course is to link engineering principles to biology and bioenergy. Prerequisites: EECE 315 or EECE 332 or approval of Instructor. Offered every spring semester. 3 credits. Levels: Graduate, Undergraduate

Applications of statistical, optimization and advanced control techniques for analysis, mathematical description, optimization and control of multivariable processes. Topics include regression analysis, linear, non-linear and dynamic programming, adaptive control. Prerequisite: EECE 361 or equivalent. Offered every other spring semester. 3 credits. Levels: Graduate, Undergraduate

Methods and tools for modeling, control, and performance analysis of asynchronous systems driven by random events. Main topics include stochastic processes, Markov chain models, queuing systems, simulation of event- and time-driven systems, security and optimal control of networked systems as controlled Markov chains. Prerequisites: A course in basic probability (probability space; conditional probability; random variables; probability mass and probability density functions; conditional distributions; expectation, variance, and moment computation.) Offered every other fall semester. 3 credits Levels: Graduate, Undergraduate

Covers the general area of discrete-time signals and the analysis and design of discrete time systems. Topics include time domain analysis, solutions of difference equations, Z-transform analysis, sampling of continuous-time signals, discrete Fourier transforms, Fast Fourier Transforms, and spectral analysis. Processing of discrete-time signals using the DFT and FFT. Design and implementation of discrete-time filters. Extensive use of software simulations in a high-level language such as Matlab. Lecture portion meets with EECE 402. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 301. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

Advanced topics in digital signal processing. Bandpass signals and bandpass sampling, multi-rate processing and filterbanks, random signals and spectrum estimation, modern DSP applications. Prerequisites: EECE 402 or equivalent and MATH 327 or ISE 261 or equivalent. Offered every spring semester. 3 credits. Levels: Graduate, Undergraduate

Theory and practice of estimating parameters for discrete-time signals embedded in noise. Application to problems in radar, sonar, emitter location and communication systems. Topics include: Cramer-Rao lower bound, minimum variance unbiased estimation, least squares estimation, maximum likelihood estimation, Bayesian estimation, and Wiener filtering. Prerequisites: EECE 402 or equivalent and ISE 261 or equivalent. Offered every other spring semester. 3 credits. Levels: Graduate, Undergraduate

Discusses the theory and practice of data compression of signals, images, and video. Techniques covered include: Quantization, Vector Quantization, Differential Schemes, Filterbanks and Subband Coding, Wavelet Transform, JPEG 2000 MPEG. Prerequisites: EECE 402 or equivalent and ISE 261 or equivalent. Offered every other spring semester. 3 credits. Levels: Graduate, Undergraduate

This course covers the fundamentals of digital audio signal processing. Topics include analog-to-digital converters and digital-to-analog converters, models for characterizing and analyzing quantization errors in digital audio, sampling rate conversion, design of filters and equalizers, algorithms for simulating room acoustics, and algorithms for implementing digital audio effects. Implementation of algorithms using Matlab is emphasized. 3 credits. Prerequisites: EECE 301 Signals and Systems, ISE 261 Probabilistic Systems I; or equivalents, or approval of instructor. Levels: Graduate

An Introduction to information theory for signal processing and communications theory. Entropy, mutual information, divergence, source coding, channel capacity, hypothesis testing and types. Prerequisite: EECE 301 or equivalent and ISE 261 or equivalent. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

Provide a broad introduction to machine learning and its applications. We will briefly review python programming, statistics, and linear algebra. Then, fundamentals of machine learning will be introduced, with topics including supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks), unsupervised learning (clustering, dimensionality reduction, recommender systems), and fundamental theories (bias/variance theory). ECE applications such as time sequence forecasting, speech recognition, and image processing will be described. Offered Spring 2023 Credits: 3 Prerequisites: ISE 261 & MATH 324, permission from instructor. Levels: Graduate, Undergraduate

Electro-optic devices and systems. Black-body, LED and laser sources, photo detectors, modulators, fiber optics, Fourier optics. Design of electro-optic systems. Lecture portion meets with EECE 474. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 323. Offered every other fall semester. 3 credits. Levels: Graduate, Undergraduate

Physics, device structure, and operation of semiconductor lasers. Band structure in solids, optical processes in semiconductors, p-n junctions, and quasi-Fermi levels; rate equation model for semiconductor lasers, static and dynamic characteristics; characteristics of distributed feedback, Bragg reflector, vertical cavity and Fabry-Perot lasers. Lecture portion meets with EECE 433. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 332. Offered every third semester. 3 credits. Levels: Graduate, Undergraduate

This course introduces fundamentals of human organ-on-a-chip systems which refer to biomedical MEMS (bioMEMS) devices containing miniaturized human organs for drug screening, disease modeling and regenerative medicine. Topics to be covered in this course will focus on applications of electrical engineering principles combined with human cell culture techniques for the design, fabrication and interrogation of organ chip models of brain, lung, intestine and eye. The aims of the course include to: (i) study microfabrication and MEMS technologies in the context of human organ-on-a-chip implement and innovations; (ii) provide general background for in vitro cell culture techniques; (iii) review electrical, optical, biological sensor techniques for the analysis of organ-on-a-chip systems; and (iv) study the exemplary applications of organ-on-a-chip technology in biomedical research and medicine. This course also provides broad discussion on recent and future trends in human organ-on-a-chip systems and bioMEMS technologies. Prerequisites: EECE 332 or permission from instructor. Credits: 3 Levels: Graduate, Undergraduate

This course covers basic solid-state physics, quantum mechanics, and semiconductor physics relevant for understanding semiconductor materials and devices. The goal of this course is for you to learn the relationship between basic science and engineering applications, and how to engineer materials at the nanoscale to enable novel electronic and photonic properties. Prerequisites: EECE 332 or permission from instructor Credits 3. Levels: Graduate, Undergraduate

This course will introduce the basics of quantum computing, including the theoretical physics background, mechanics of creation and manipulation of physical qubits, the mathematical basis for qubit gates, and quantum computing and algorithms. When Offered: Spring 2023 Credits: 3 Prerequisites: EECE 212 and/or permission from instructor. Levels: Graduate, Undergraduate

Topics in wireless communications such as cellular radio, PCS and wireless LAN. Cellular system design, frequency reuse, channel assignment, handoff, power control, cell splitting, sectorization, system capacity. Radio propagation, multi-path and fading, signal design principles, spread-spectrum modulation techniques, receiver/transmitter architectures. Multiple access for wireless systems: FDMA, TDMA, CDMA, SDMA. Wireless networking. Prerequisite: EECE 377 or equivalent. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

Fundamentals of information in digital communication systems; digital passband modulation and demodulation; channel coding; error detection; spread spectrum; signal space representation; bit error rate. Digital modem design and implementation and final project. Lecture portion meets with EECE 477. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 377 or equivalent. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

This course will cover several topics in the area of computer architecture. We will discuss various concepts behind the designs of current mircroprocessors. In particular, the topics that will be covered in the course are: RISC machines and instruction set architectures, performance evaluation, pipelined architecture, static and dynamic scheduling, instruction-level parallelism, advanced pipelining, speculative execution, memory hierarchy and organization, multi-processing, compiler techniques (and more). Lecture portion meets with EECE 452. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 351 or equivalent. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

This is an introduction level computer network architecture course for senior/graduate students. The goal is to provide the students with a comprehensive picture of the technologies behind the Internet and applications on top of it. Starting with a brief review of some basics of networking, we will discuss from the lowest levels of packet transmissions through the highest levels of application software under the umbrella of the TCP/IP architecture. Emphasis will be given on the network architecture, components and design principles. Lecture portion meets with EECE 453. Extra assignments, and/or final project will be required at the graduate level. Prerequisites: Basic knowledge of probability and statistics. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

Microcontroller based embedded systems design and analysis. Bare metal assembly and C software development for hardware and software integration. Driver based hardware abstraction and input/output synchronization. Sensor hardware integration, information extraction and fusion. Microcontroller applications and project. Lecture portion meets with EECE 458. Extra assignments, and/or final project will be required at the graduate level. Prerequisites: EECE 351 or equivalent and CS 211. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

This course explores and analyzes the individual elements required to design a software-defined radio (SDR) receiver. Optimizations and tradeoffs are discussed as the receiver elements are integrated together. For the final project, the functional elements are integrated into a digital receiver system and the performance of the receiver is assessed. Topics include: modulation and demodulation, signal sampling, pulse shaping, bandwidth and data rate, synchronization, linear equalization, coding and decoding, timing recovery, and carrier recovery. Matlab is used to model the receiver elements and to implement the final project. Lecture portion meets with EECE 414. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 459 or EECE 377 or equivalent. Offered every spring semester. 3 credits. Levels: Graduate, Undergraduate

Introduction to codes and ciphers, information security, and mathematical basis of encryption. Cryptanalysis (code-breaking), modern block and stream ciphers, public-key cryptography, protocols, security engineering and threat management. Lecture portion meets with EECE 405. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: Familiarity with a computer programming language is necessary to complete assignments. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

An introduction to the modern field of covert communication using digital media. General principles of covert communications in digital images and detection of hidden data in digital media files (statistical tests, signal estimation). Steganographic security, capacity and detectability. Universal blind steganayzers based on machine learning. Forensic steganalysis. Prerequisites: Knowledge of MATLAB and basics of signal processing. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

Convex sets, functions, and problems; basics of convex analysis; least-squares, linear, quadratic, geometric, and semi-definite programs; duality theory; numerical linear algebra and algorithms; MATLAB-based tools for convex optimization; applications to in signal processing, networking, control, circuit design, etc. Prerequisites: EECE 506 or working knowledge of linear algebra, exposure to probability, and some familiarity with MATLAB, or Instructor permission. Offered every third spring semester. 3 credits Levels: Graduate, Undergraduate

Course on statistical signal detection techniques and their applications in digital forensics. Lectures are interleaved with hands-on projects to show the students the usefulness of theoretical concepts introduced during lectures. Students will become familiar with an important forensic method for digital media that identifies digital cameras and manipulated images using the so-called sensor fingerprint. From the technical point of view, the course contains the following topics: Binary and multiple hypothesis testing, Neyman-Pearson theorem, Bayesian risk minimization, likelihood ratio test. Detection of deterministic signals and random signals, matched and generalized matched filter. Gaussian and non-Gaussian noise. Detection of signals with unknown parameters and unknown noise parameters, generalized likelihood ratio test, universally most powerful test. Basics of parameter estimation theory. The techniques will be demonstrated via hands-on projects drawn from the field of digital forensics (digital watermarking and sensor fingerprints). Prerequisite: Basic statistics. Offered every spring semester. 3 credits. Levels: Graduate

Cyber-physical systems (CPS) represent a new class of systems that bring together sensing, computation, communication and control to enable continuous interactions with physical processes. Application areas are as diverse as aerospace, civil infrastructure, energy, manufacturing, transportation most of which are safety-critical. The availability of cheap communication technologies such as the Internet, makes such infrastructures to susceptible to cyber-threats. The goal of this class is to provide a unified overview of CPS security issues, from the perspective of control, communication and game theories, relating to various CPS including industrial control systems and those considered critical infrastructure systems. It will also introduce students to concepts in optimization, decentralized decision making in teams and games, and the interconnections between information and decision making, and networked control systems. Prerequisites: EECE 212, ISE 261, or approval of instructor. Offered every other fall semester. 3 Credits. Levels: Graduate, Undergraduate

This course will provide an introduction to the field of reinforcement learning (RL). The topics that will be covered (time permitting) include but not limited to Markov Chains; MDPs; Value Functions; Policy Iteration and Value Iteration; Monte Carlo Methods; Temporal Difference (TD) Learning; (Linear) Function Approximation; SARSA; Q-Learning; TD(); Actor-Critic Methods; Neural Networks, Backpropagation and Applications to RL; Other topics (e.g., Multi-Agent RL, RL Theory; Deep Reinforcement Learning). This course will emphasize on hands-on experiences, students are expected to become well versed in key ideas and techniques for RL through a combination of lectures, written and coding assignments. Students will advance their understanding and the field of RL through a project. Prerequisites: Calculus and Linear Algebra; Basic Probability and Statistics; Python. 3 credits. Offered in the Spring. Levels: Graduate, Undergraduate

This course will provide an overview of the components of system on a chip (SOC) design from initial technology and architectural choices, to hardware/software design techniques (e.g., data/control flow modeling and implementation, embedded cores and coprocessors, hardware/software communication), as well as SOC implementation issues (e.g., performance, core selection, on-chip communication networks, power management, package constraints, and cost). Also covered are SOC design and implementation processes (e.g., functional integration, simulation, clocking strategies, timing, design for test, and debug strategies). Lecture portion meets with EECE 438. Extra assignments, and/or final project will be required at the graduate level. Prerequisites: EECE 315 and 287. Offered every spring semester. 3 credits. Levels: Graduate, Undergraduate

VLSI design, synthesis and test using hardware description language (HDL) at the register-transfer level (RTL). HDL programming and simulation basics, followed by advanced HDL programming for synthesis and test benching. Principles of RTL synthesis introduced. Design and synthesis of digital systems to meet constraints. Pre-synthesis and post-synthesis verification using simulation. Commercial synthesis tool discussed in detail. Lecture portion meets with EECE 451. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 351 or equivalent. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

The topics include the principles of MOSFET transistors, characteristics of CMOS digital circuits, layout design and process, performance analysis of CMOS gates, circuit design styles using MOSFET, performance, area and power optimization of CMOS circuits. Commercial design and simulation tools will be used in the class. Laboratory assignments include design, layout, extraction and simulation.Lecture portion meets with EECE 455. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 351 or equivalent. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

Gate level and physical level design of a complex system, such as RISC processor (including the ALU and memory) is discussed. Advanced topics in logic-level design, such as high performance design, dynamic logic, low power design, asynchronous logic, interconnect analysis, cross talk issues, bus architecture, layout floor planning, and placement and routing, will be covered. Students will be asked to use Cadence physical design, analysis, and simulation tools. Prerequisite: EECE 574. Offered every spring semester. 3 credits. Levels: Graduate, Undergraduate

Multidisciplinary Introduction to Microfabrication: Introduction to clean room tools, procedures, and theory through the fabrication and characterization of various devices from the fields of electrical engineering, mechanical engineering, physics and chemistry. Fabrication of the devices will cover most clean room tools and techniques, including lithography based patterning methodologies; chemical vapor deposition; sputtering; thermal and e-beam evaporation; thermal oxidation; reactive ion etching; ion implantation; and wet chemical processing. The accompanying lecture will cover the theory of the tools used. Lecture portion meets with EECE 431. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 332 or an equivalent course in basic semiconductor device physics. Offered every spring semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Graduate, Undergraduate

Multidisciplinary Introduction to Microfabrication: Introduction to clean room tools, procedures, and theory through the fabrication and characterization of various devices from the fields of electrical engineering, mechanical engineering, physics and chemistry. Fabrication of the devices will cover most clean room tools and techniques, including lithography based patterning methodologies; chemical vapor deposition; sputtering; thermal and e-beam evaporation; thermal oxidation; reactive ion etching; ion implantation; and wet chemical processing. The accompanying lecture will cover the theory of the tools used. Lecture portion meets with EECE 431. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 332 or an equivalent course in basic semiconductor device physics. Offered every spring semester. 4 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Graduate, Undergraduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate, Undergraduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate, Undergraduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate, Undergraduate

In this course, we focus on the introduction of neural networks as well as their applications in deep learning. Fundamentals of neural networks and deep learning will be discussed, including multilayer perceptron, back-propagation algorithm, regularization theory, convolutional neural networks, recurrent neural networks, and reinforcement learning. After a brief overview of the python programming language and statistical signal processing, neural networks and their applications are followed. Application topics in speech recognition, image and language processing will be described. A final project will let students to work on the applications of deep learning or participate in online deep learning competitions. Prerequisites: EECE301 or equivalent signals and systems knowledge 3 credits, offered in the Fall Levels: Graduate, Undergraduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate, Undergraduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate, Undergraduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate, Undergraduate

This course will cover topics related to renewable energy generation (solar photovoltaic cells), and storage (battery, supercapacitors and fuel cells) devices. The main topics include organic and inorganic photovoltaics, super-capacitors, and batteries. The course will also briefly discuss fuel cells and their application in power generation and hydrogen production. The course will emphasize the electronic and optical properties of the energy materials together with the theoretical and experimental aspects of device design. In addition, the course will also cover power system designs including PV cells and batteries for both grid connectivity and stand-alone systems. Students will also be asked to present a seminar on recent research reports published in these fields. Prerequisites: ECE332 (Semiconductor Devices) or equivalent. Offered in Spring. 3 Credits. Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate, Undergraduate

Quantum mechanical description of materials is important to understand structure-property-performance relationships in materials science. Theoretical computation is a power tool and complementary approach to experiments. This course will firstly provide an overview of quantum mechanics and solid-state physics that are important to the understanding of basic concepts underlying the computational methods. We will then discuss practical implementations: students will learn to run the actual first-principles computational code VASP (https://www.vasp.at/) on supercomputers, interpret and present the results. We will illustrate examples to show how computational methods can be used to understand materials structures, defects, and functions for real-world applications, including recent literature in renewable energy, electronics, and quantum information. Credits 3 Levels: Graduate, Undergraduate

Implantable biomedical electronics is the application of engineering principles to biology, medicine, and health. These novel devices have become an important set of tools in medical technologies and widely employed for the prevention, diagnosis, and treatment of disease in the human body, for patient rehabilitation, and for improving health. In this course, we cover the fundaments of implantable bioelectronic devices and integrated microelectronics for biomedical and implantable systems. Some of topics include prosthetic devices, neural interfaces, brain implants, implantable biosensors, drug delivery systems and more. This course also provides in depth discussion on human physiology and pathophysiology for understanding the potential impact of this emerging technology on patient care and clinical outcomes. Prerequisites: EECE315 “Electronics I” Offered in the Fall. 3 Credits. Levels: Graduate

Students will learn undergraduate instruction aspects of a formal course under the direct supervision of a faculty member and perform substantial course development work. This may include design of new lecture materials, instructional techniques, assignments, and laboratory experiments combined with presentations and/or laboratory supervision. Written documentation of newly developed materials is submitted to the course instructor. May count for one M.S. elective and must be taken with normal (letter) grade option ONLY. It may also be used by Ph.D. students to satisfy the teaching proficiency requirement. Prerequisites: Permission of course instructor. Offered in the Fall and Spring. 3 Credits Levels: Graduate

This course is a 32-week in-house course taught at BAE Systems for students enrolled in the BAE ELDP program only and devoted to a broad review of engineering fundamentals, with emphasis on interdisciplinary topics related to Electronic Systems products and processes, technologies, applications, and problem solving techniques. Coursework includes a team-project and presentation to engineering management. Offered every spring semester. 6 credits. Levels: Graduate, Undergraduate

This course is a 16-week in-house course taught at BAE Systems for students enrolled in the BAE ELDP program only and devoted to challenging students with problems very similar to those frequently facing Electronic Systems engineers. Coursework includes a technical project requiring the application of systems, software, and hardware engineering skills. Offered every fall semester. 3 credits. Levels: Graduate, Undergraduate

Engineering work experience in industry. Daily logbook, memo progress reports, and formal final report required. Signature of faculty advisor and graduate director required prior to registration. Offered every semester. Variable credit. Levels: Graduate, Undergraduate

Independent study or graduate laboratory exercises supervised by electrical/computer engineering faculty member. Signature of instructor required. Offered every semester. Variable credit. Levels: Graduate, Undergraduate

Hardware and software design and development or other project as defined by a Learning Contract, approved by major professor and project advisor. Seminar presentation required. Formal report submitted to the Project advisor. Signature of advisor required prior to registration. Offered every semester. Variable credit. Levels: Graduate, Undergraduate

Mentoring in the methods of research. Theoretical analysis, computer modeling, software and hardware development and experimentation as determined by a Thesis Committee, faculty advisor, second reader or co-advisor and department chair. Oral defense. Preparation of journal article required. Thesis submitted to Graduate School electronically for the University Library. Signature of advisor required prior to registration. Offered every semester. Variable credit. Levels: Graduate, Undergraduate

This module deals extensively with the design of high frequency high efficiency power electronic converters for AC-DC, DC-DC, and DC-AC, using pulse width modulation (PWM) and resonant energy conversion techniques. This module will make the student aware of the fundamental considerations needed to design power electronic converters in an industrial environment and conforming to different industrial standards especially in terms of electromagnetic interference (EMI)/Efficiency/Line harmonics (AC-DC). Prerequisites: EECE 419, and EECE 506 or EECE 507, or equivalent. Offered in the Fall. 3 credits. Levels: Graduate, Undergraduate

This is a research oriented class that will focus on the state of the art in the network security area. The primary goal of the class is to expose students to cutting edge research works and prepare them for carrying out research independently. Topics include: Sources of Network Vulnerabilities; Overview of Network Security Problems; Standard Internet Security Solutions; Internet Infrastructure Protection; Security in Wireless Sensor Networks; Security Architecture of Grid Computing; Trust, Security and Privacy in P2P/Pervasive Computing Environments; Reconfigurable Hardware Implementation of Security Solutions. Prerequisite: EECE 553 or equivalent. Offered every spring semester. 3 credits. Levels: Graduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate

Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. 3 credits. See semester schedule for current offering. Levels: Graduate, Undergraduate

In this course, we focus on the introduction of neural networks as well as their applications in deep learning. Fundamentals of neural networks and deep learning will be discussed, including multilayer perceptron, back-propagation algorithm, regularization theory, convolutional neural networks, recurrent neural networks, and reinforcement learning. After a brief overview of the python programming language and statistical signal processing, neural networks and their applications are followed. Application topics in speech recognition, image and language processing will be described. A final project will let students to work on the applications of deep learning or participate in online deep learning competitions. Prerequisites: EECE301 and EECE506 or EECE507 or equivalent or permission of instructor. Offered in the Fall. 3 credits Levels: Graduate, Undergraduate

Independent study supervised by electrical/computer engineering faculty member. Student must obtain consent of instructor, who then determines description of program and number of credits. Offered every semester. Variable credit. Levels: Graduate

Exploratory research oriented toward PhD dissertation. Offered every semester. Variable credit. Levels: Graduate

Research for and preparation of PhD dissertation. Offered every semester. Variable credit. Levels: Graduate

Required to maintain matriculation through any spring or fall semester when no other courses are taken. If the minimal one-credit registration is not maintained, student must reapply for admission. Offered every semester. Variable credit. Levels: Graduate

May be used by all funded graduate assistants to obtain additional credits for full-time status. Research or teaching supervised by faculty advisor. Offered every semester. Variable credit. Levels: Graduate