EE - Electrical Engineering

Courses numbered 500 to 799 = undergraduate/graduate. (Individual courses may be limited to undergraduate students only.) Courses numbered 800 to 999 = graduate.

EE 577.  Special Topics in Electrical and Computer Engineering   (1-4).

New or special courses presented on sufficient demand. Repeatable for credit. Prerequisite: departmental consent.

EE 577L.  Renewable Energy Engineering   (3).

Analysis and design of renewable energy systems, including solar, wind, hydroelectric, geothermal and biomass systems. Analysis and design of energy storage systems that integrate with renewable energy systems. Integration of renewable energy systems with the electric power supply system. Prerequisites: PHYS 314 and EE 282.

EE 577M.  Real-Time Signal Processing Applications   (3).

In most digital signal processing operations, it is assumed that we have sampled signals which are considered as digital signals. Often in classroom educations, these signals are usually stored for subsequent retrieval or synthesized when needed, for convenience for demonstrations or computer-based assignments. However, this does not allow for real-time processing of the signals. Real-time processing means guaranteed delivery of data by a certain time. This undergraduate elective course is hardware based with hands-on simulations to introduce students to the analysis, design, and implementation of real-time digital signal processing (DSP) applications. The course first briefly introduces basic DSP theory, then focuses on a practical, step-by-step framework that provides hands-on experience in real-time DSP to reinforce the basic DSP theory. Students are expected to learn how to use/apply the DSP theory in real-time applications. Prerequisites: EE 383 or equivalent, CS 211. Corequisite: EE 577ML.

EE 585.  Senior Design Project I   (2).

3 Lab hours. Design project under faculty supervision chosen according to the student's interest. Does not count toward a graduate degree in electrical engineering, computer engineering or computer science. For undergraduate credit only. This class should be taken in the semester prior to the one in which the student is going to graduate. Prerequisites: senior standing, CS 480 or EE 492. Pre- or corequisite: PHIL 354 or 385.

EE 586.  Introduction to Communication Systems   (4).

3 Classroom hours; 2 Lab hours. Fundamentals of communication systems; models and analysis of source, modulation, channel and demodulation in both analog and digital form. Reviews Fourier series, Fourier transform, DFT, probability and random variables. Studies in sampling, multiplexing, AM and FM analog systems, and additive shite Gaussian noise channel. Additional topics such as PSK and FSK digital communication systems covered as time permits. Prerequisites: EE 383, IME 254. Corequisite: EE 586L.

EE 588.  Advanced Electric Motors   (3).

Advanced electric motor applications and theory. Includes single-phase motors, adjustable speed AC drive applications and stepper motors. Prerequisite: EE 488.

EE 595.  Senior Design Project II   (2).

3 Lab hours. Continuation of EE 585. For undergraduate credit only. Will not count toward a graduate degree in electrical engineering, computer engineering or computer science. Prerequisite: EE 585.

EE 598.  Electric Power Systems Analysis   (3).

Analysis of electric utility power systems. Topics include analysis and modeling of power transmission lines and transformers, power flow analysis and software, and introduces symmetrical components. Prerequisite: EE 488.

EE 610.  Introduction to Quantum Computing   (3).

Introduces the theory and practice of quantum computing. Topics covered include the basics of quantum mechanics, Dirac notation, quantum gates and circuits, entanglement, measurement, teleportation and algorithms. Prerequisite: MATH 511.

EE 684.  Introductory Control System Concepts   (3).

Cross-listed as ME 659. Introduces system modeling and simulation, dynamic response, feedback theory, stability criteria, and compensation design. Prerequisites: (1) EE 282 and MATH 555, or (2) EE 383.

EE 688.  Power Electronics   (4).

3 Classroom hours; 2 Lab hours. Deals with the applications of solid-state electronics for the control and conversion of electric power. Gives an overview of the role of the thyristor in power electronics application and establishes the theory, characteristics and protection of the thyristor. Presents controlled rectification, static frequency conversion by means of the DC link-converter and the cyclo converter, emphasizing frequency, and voltage control and harmonic reduction techniques. Also presents requirements of forced commutation methods as applied to AC-DC control and firing circuit requirement and methods. Introduces applications of power electronics to control AC and DC motors using new methods such as microprocessor. Prerequisites: EE 383, 488, 492. Corequisite: EE 688L.

EE 697.  Electric Power Systems Analysis II   (3).

Analysis, design, modeling and simulation of high-voltage electric power transmission systems and rotating generators. Simulations include short circuit studies, economic dispatch and transient stability. Prerequisite: EE 598.

EE 726.  Digital Communication Systems I   (3).

Presents the theoretical and practical aspects of digital and data communication systems. Includes the modeling and analysis of information sources as discrete processes; basic source and channel coding, multiplexing and framing, spectral and time domain considerations related to ASK, PSK, DPSK, QPSK, FSK, MSK, and other techniques appropriate for communicating digital information in both base-band and band-pass systems; intersymbol interference, effects of noise on system performance, optimum systems and general M-ary digital systems in signal-space. Prerequisites: EE 586 and 754.

EE 754.  Probabilistic Methods in Systems   (3).

Course in random processes designed to prepare the student for work in communications controls, computer systems information theory and signal processing. Covers basic concepts and useful analytical tools for engineering problems involving discrete and continuous-time random processes. Discusses applications to system analysis and identification, analog and digital signal processing, data compression parameter estimation, and related disciplines. Prerequisites: EE 383 and IME 254.

EE 777.  Selected Topics in Electrical Engineering   (1-4).

New or special courses presented on sufficient demand. Repeatable for credit. Prerequisite: departmental consent.

EE 777C.  Network Programming   (1-4).

Introduces techniques for developing TCP and UDP network clients, servers and applications. Topics covered include sockets, client/server design alternatives, concurrent processes and threads, web applications, and security. Programming-intensive course that assumes some experience with programming in a high-level language. Prerequisite: CS 300 (or an equivalent course).

EE 777OL.  Digital Communications I Lab   (1).

Lab objective is for the students to implement and explore each block in a wireless communications system signal chain by combing LabVIEW software and the National Instrument (NI) Universal Software Radio Peripheral (USRP) hardware. Covers pseudorandom bit generation, path loss in wireless radio frequency (RF) communication channel, forward error correction (FEC) channel coding, wireless digital communications modulation, demodulation, synchronization (timing recovery), bit error rate (BER), and a multiple-input and single-output (MISO) wireless system.

EE 782.  Digital Signal Processing   (3).

Presents the fundamental concepts and techniques of digital signal processing. Time domain operations and techniques include difference equations and convolution summation. Covers Z-transform methods, frequency-domain analysis of discrete-time signals and systems, discrete Fourier transform, and fast Fourier transform. Emphasizes the frequency response of discrete-time systems and the relationship to analog systems. Prerequisite: EE 383.

EE 784.  Digital Control Systems   (3).

Studies the effects of sampling and quantization, discrete systems analysis, sampled-data systems and Z-domain and state space design. Prerequisite: EE 684 or ME 659.

EE 792.  Linear Systems   (3).

Reviews mathematics relevant to state-space concepts. Formulation of state-variable models for continuous-time and discrete-time linear systems. Concepts of controllability, observability, stabilizability and detectability. Pole placement and observer design. State transformation techniques and their use in analysis and design of linear control systems. Prerequisite: EE 684 or ME 659.

EE 796.  Electric Power Distribution   (3).

Analysis, design, modeling and simulation of radial medium-voltage electric power distribution systems. Simulations include power flow and short circuit. Prerequisite: EE 598.

EE 824.  Cooperative Communication Systems   (3).

Studies cooperative communication systems in which the users collaborate in their data transmissions. Cooperative transmission is regarded as an efficient, low cost technique to obtain the advantages of multiple antennas. Introduces fundamental cooperative protocols as well as recent advanced topics in relay communication systems. Prerequisites: EE 726, 754 or equivalent.

EE 826.  Digital Communication Systems II   (3).

Studies modern digital communication systems. Discusses topics such as carrier and symbol synchronization techniques, fading multipath channels, frequency-hopped spread spectrum systems, smart antenna array systems, space time codes (STC), space-time block codes (STBC), multi-input multi-output (MIMO), orthogonal frequency division multiplexing (OFDM) systems, and multi carrier code division multiple access (MC-CDMA) communication. Prerequisite: EE 726.

EE 836.  5G Wireless Communications   (3).

Covers the fundamental and advanced technologies for future fifth generation (5G) wireless communication systems. Studies the emerging wireless communication technologies such as small cells, coordinated multipoint (CoMP), massive multiple-input multiple-output (Massive-MIMO), millimeter wave (mmWave), device-to-device (D2D), etc. Combinations of these technologies may support future explosive higher data rates, lower latency, and larger coverage area. Prerequisite: EE 726.

EE 856.  Information Theory   (3).

Introduces information theory for students of communication theory, computer science and statistics. Introduces the definitions of entropy, relative entropy and mutual information. Discusses asymptotic equipartition property, entropy rates of a stochastic process, channel capacity, differential entropy and Gaussian channel. Prerequisite: EE 754.

EE 864.  Multi-Service Over IP   (4).

3 Classroom hours; 2 Lab hours. Advanced networking course; deals with challenges and solutions associated with sending voice, video and data (multi-service) over IP. Includes telephony signaling, call routing and dial plans, measuring voice quality, voice digitization and coding, quality of service issues, and current research. Hands-on lab allows students to design, troubleshoot and test different VOIP scenarios. Prerequisite: CS 764.

EE 876.  Master's Thesis   (1-6).

Repeatable for credit up to 6 credit hours. Prerequisite: prior consent of MS thesis advisor.

EE 877.  Special Topics in Electrical Engineering   (2-3).

New or special courses are presented under this listing on sufficient demand. Repeatable for credit. Prerequisite: departmental consent.

EE 877AA.  Information Theoretic Security   (3).

Presents a framework for secure communication, which makes no assumptions on the computational power of a potential adversary. Begins with fundamental tools from information theory and cryptography, which provide the basis for modern research on security at the physical layer and secret-key generation. Various models and applications are discussed. Prerequisite: IME 254.

EE 877AB.  Signal Processing and Machine Learning for Brain-Computer Interface   (3).

Presents a framework on machine learning algorithms in general, with a focus on brain-computer interface system. Students learn machine learning concepts such as feature extraction, and classification, and get a hands-on experience with implementing signals into feature spaces, such as principal component analysis, and classifiers such as support vector machine. Prerequisites: EE 782 and EE 754.

EE 877S.  Detection and Estimation   (3).

Deals with extracting information from observed signals. Observations are typically distorted or corrupted due to various reasons. Therefore, detection and estimation problems are formulated in a probabilistic framework, where unknown behavior is assumed to be random. The objective is to extract information about some phenomenon related to a given random observation. Detection problems aim at deciding among a finite number of possibilities. Estimation problems aim at finding estimated values of certain quantities that are not observed directly. Detection and estimation theory has a wide range of applications, including networking and communication systems, power systems and control systems. Prerequisite: EE 754 or departmental consent.

EE 877X.  EECS Graduate Seminar   (1).

Provides an opportunity to learn about contemporary research and technologies in electrical engineering, computer engineering and computer science. Students are expected to strengthen their topics of current interest and explore beyond their own research area thorough oral and written presentations.

EE 877Y.  Nonlinear Systems   (3).

Focuses more on methods to analyze nonlinear systems, as opposed to control of nonlinear systems. Topics include: (1) introduction to nonlinear systems, (2) one-dimensional nonlinear system: bifurcations (saddle-node, transcritical and pitchfork bifurcations), (3) two-dimensional nonlinear systems: phase portraits, limit cycles, bifurcations (saddle-node, transcritical, pitchfork and Hopf bifurcations), (4) weakly nonlinear oscillators (Van der Pol equation and Duffing equation), method of averaging, (5) Lyapunov analysis, and (6) describing function methods. Prerequisite: EE 792.

EE 877Z.  Nano Communications   (3).

Nano communication is the exchange of information at the nanoscale and it is at the basis of any wired/wireless interconnection of nano machines, enabling a plethora of applications in the biomedical, environmental, industrial and military fields. Presents different approaches to realize this type of communication through electromagnetic, ultrasonic and magnetic-induction communications. Each of these alternatives is described by following a bottom-up approach, i.e., first, an overview of its specific enabling device technology is presented and, second, the state of the art in terms of communication channel modeling, physical layer techniques (e.g., modulation, coding, transmission) and link layer solutions (e.g., medium access control, error control) is described. In addition to the theoretical knowledge that is assessed in exams, students are assigned independent group projects focused in the different core areas of the field. Through the projects, students have the chance to learn and practice COMSOL Multi-physics, MATLAB and LabVIEW. At end of the semester, students write a technical report and orally present their work in class. Course provides students with the necessary knowledge to work in a cutting-edge research field, at the intersection of nanotechnologies and information and communication technologies.

EE 878.  Master's Directed Project   (1-4).

Project conducted under the supervision of an academic advisor for the directed project option. Requires a written report and an oral presentation on the project. Prerequisite: academic advisor's consent.

EE 885.  Robust Control Systems   (3).

When applying control theory to real systems, engineers are faced with uncertainties in plant models, plant disturbances and sensor noise. Robust control theory is an optimal approach for applying feedback control theory to systems with these uncertainties. Students completing this course should be capable of analyzing a linear control system in terms of performance and robustness, designing controllers and estimators using H-infinity optimization, and reducing plant model and/or controller implementation orders. Prerequisites: EE 792; EE 684 or ME 659.

EE 886.  Error Control Coding   (3).

Introduces error control codes, including Galois fields, linear block codes, cyclic codes, Hadamard codes, Golay codes, BCH codes, Reed-Solomon codes, convolutional codes, Viterbi decoding algorithm, Turbo codes, and ARQ protocols. Applies to digital 3G and 4G cellular and satellite communication systems. Prerequisite: EE 726.

EE 893.  Optimal Control   (3).

Reviews mathematics relevant to optimization, including calculus of variations, dynamic programming, and other norm-based techniques. Formulates various performance measures to define optimality and robustness of control systems. Studies design methods for various classes of systems, including continuous-time, discrete-time, linear, nonlinear, deterministic and stochastic systems. Prerequisite: EE 792.

EE 897.  Operation and Control of Power Systems   (3).

Acquaints electric power engineering students with power generation systems, their operation in economic mode, and their control. Introduces mathematical optimization methods and applies them to practical operating problems. Introduces methods used in modern control systems for power generation systems. Prerequisite: EE 598.

EE 898.  Electric Power Quality   (3).

Measurement, analysis, modeling, simulation and mitigation of electric power quality on medium- and low-voltage distribution systems. Prerequisite: EE 697.

EE 976.  PhD Dissertation   (1-16).

Repeatable for credit. Prerequisite: admission to doctoral aspirant status.

EE 981.  Cooperative Education   (1).

Work-related placement with a supervised professional experience to complement and enhance the academic program. Intended for master's-level or doctoral students in electrical engineering. Repeatable for credit up to 8 credit hours. May not be used to satisfy degree requirements. Prerequisites: departmental consent and a graduate GPA of at least 3.000.

EE 986.  Wireless Spread-Spectrum Communication   (3).

Explains what spread-spectrum communication is and why direct-sequence code-division multiple access (DS-CDMA) spread-spectrum is used for wireless communication. Studies the block diagrams of the IS-95 forward and reverse wireless communication links under multi-path mobile fading environment using analysis techniques and simulation. Analyzes pseudo-noise (PN) signal generation, the band-limited waveform shaping filter, convolutional coding, interleaver, Walsh code orthogonal modulation, Rake finger receivers, no coherent Walsh orthogonal suboptimal demodulation, other simultaneously supportable subscribers, and third generation CDMA. Prerequisite: EE 726.