Master of Science in Electrical and Electronics Engineering

Prerequisite: Grad Standing

This course covers solution of eigenvalues and eigenvector decomposition, Laplace transform, partial differential equations. The course also covers topics in advanced numerical analysis techniques and their applications for solving advanced engineering problems. The course includes initial-value problems for ordinary differential equations, approximation theory, numerical solutions of nonlinear systems of equations. The course deals with various advanced examples from different engineering disciplines.

Prerequisite: Grad Standing

This course covers students learning activity on how to apply the engineering research process and methods of inquiry to solve engineering problems; doing literature review in the areas of interest, this involves critiquing current research work. Students learn legal and ethical issues related to protecting and exploiting research, more specifically, intellectual Property rights. They will also learn how to communicate findings in specific engineering formats to specialist audiences. Students will learn basic project management and teamwork skills in addition to research ethics. Course project will allow the students to apply research methodology components on research problems of their choice. Students are expected to present and defend their research proposals.

Prerequisite: Grad Standing

The course deals with formulation, solution and implementation of optimization models such as linear programming, dynamic programming, integer programming, quadratic programming, convex programming, geometric programming and unconstrained optimization for analyzing complex systems problems in industry.

Students are required to attend seminars given by faculty members, visitors, and fellow graduate students. Each student is also required to present a seminar outlying the research topic of the master thesis.

The student has to undertake and complete research topic under the supervision of a faculty member. The thesis work should provide the student with an in-depth understanding of a research problem in Electrical-Electronics Engineering. It is expected that the student, under the guidance of the supervisor, will be able to conduct research somewhat independently, and may also be able to provide solution to that problem.

Prerequisite: Grad. Standing

This course deals with modeling and control of linear multivariable systems. State space representation of multivariable systems. Linear algebra background. Modeling of multivariable systems. Realization theory. Controllability and observability. Minimality. Stability. State feedback and Estimation. Separation theorem. Output Feedback. Compensation.

Prerequisite: Grad. Standing

This course deals with nonlinear systems dynamics. It includes: Linearization, iteration and perturbation analysis; Phase plane method. Describing functions analysis; Limit cycles; Lyapunov stability; Input/output stability; Input/output linearization; Stabilization and control of nonlinear systems.

Prerequisite: Grad. Standing

This course deals with methods for building mathematical models of systems. Review of transient and frequency response analysis. Regression analysis. Parameterization of models. Maximum likelihood and prediction error methods. Mathematical and experimental modeling. Model validation. Model approximation. Real-time identification. Closed loop identification. Introduction to nonlinear system identification.

Prerequisite: Grad. Standing

This course deals with advanced and emerging topics that are selected from the area of Control and Automation. Contents of the course will be provided one semester before it is offered.

Prerequisite: Grad. Standing

This course deals with robust feedback control design for uncertain systems. Elements of robust feedback control theory. Norms of signals and systems. Performance specifications. Stability and performance of feedback systems. Performance limitations. Model uncertainty and robustness. Parametrization of stabilizing controllers. Loop transfer recovery robust design. H-infinity control and filtering.

Prerequisite: Grad. Standing

This course deals with robust model predictive control design theory. Predictive control concept. Process models and prediction. Optimization criterion. Predictive control law. Performance and robustness. Minimum cost horizon. Disturbance model. Overview of well-Known predictive controllers. Tuning of predictive controller design parameters. Predictive control with output constraints. Implementation issues. Industrial case studies.

Prerequisite: Grad. Standing

This course covers some recent and timely topics in power systems. These topics includes dynamic model of synchronous machines. Excitation and governor systems. Nonlinear and linear modeling of single machine infinite bus systems. Stability analysis and control design. Direct method of stability determination. Multimachine systems modeling. Power systems dynamic equivalent circuits.

Prerequisite: Grad. Standing

This course covers the steady state and dynamic analysis of electrical AC and DC machines. Field orientation theory and control, (Direct and quadrature axis transformation) for AC machines. In addition to some recent control strategies for DC and AC machines by using linear state space representation and simulation of electromechanical systems.

Prerequisite: Grad. Standing

This course deals with advanced and emerging topics that are selected from the area of Power system. Contents of the course will be provided one semester before it is offered.

Prerequisite: Grad. Standing

The course provide review of power semiconductor devices: thyristors, GTO, power transistor, and MOSFET. Power control converters. AC voltage Controllers, PWM techniques, Multilevel inverters, Drive specifications. Rectifier control of DC motors. Fully controlled single-phase and three-phase drives. Multiquadrant operation of DC motors. Closed-loop control of DC motors. Induction motors by voltage controllers. Frequency controlled induction motor drives. Slip power control. Self-controlled synchronous motors. Current/voltage source inverter drives. Introduction to microcomputer control of AC and DC drives.

Prerequisite: Grad. Standing

This course covers the fundamental of communication system engineering. It provides an overview of probability and random processes, autocorrelation, spectral density and noise in linear systems. Additionally, it covers PAM and PCM systems, detection of binary and M-ary signals in Gaussian noise, matched filter and correlator receivers. Moreover, the course deals with error performance for binary and M-ary systems, pulse shaping, band pass modulation and demodulation techniques, channel capacity and other selected topics in digital communications.

Prerequisite: Grad. Standing

This course provides a foundation on the theory of detection and estimation. It covers several binary and M-ary detection and hypothesis testing techniques including maximum likelihood, Newman Pearson, minimum probability of error, maximum a posteriori probability, Bayes decision and mini-max detection. It also covers the various parameter estimation techniques including weighted least squares, BLUE, Maximum likelihood, minimum mean square error (MMSE) estimation. The course also covers signal estimation and filtering techniques including Wiener filtering and Kalman filtering and estimation, with applications to communication systems.

Prerequisite: Grad. Standing

This courses focuses on the fundamental limits on data compression, and on transmission over communication channels. The course topics include the information measures of entropy and mutual information, source coding theory, data compression, Huffman coding, Lempel-Ziv codes, arithmetic codes, the rate distortion theory, the channel capacity theory, and Gaussian channels.

Prerequisite: Grad. Standing

The course covers finite field arithmetic, linear codes, block codes, cyclic codes, BCH and Reed-Solomon codes, encoding and decoding methods, performance analysis of block and cyclic codes, Convolutional codes, Trellis representation, the Viterbi algorithm, performance analysis of convolutional codes, Coded modulation, Turbo codes.

Prerequisite: Grad. Standing

This course deals with advanced and emerging topics that are selected from the area of Communication. Contents of the course will be provided one semester before it is offered.

Prerequisite: Grad. Standing

This course covers high frequency circuits with special attentions to integrated circuits at both transistor and system levels. The course includes high frequency analog building blocks like the current conveyors and the current feedback operational amplifiers, high-speed amplifiers and tuned amplifiers, high frequency oscillators and the phase locked loop (PLL). All the course topics will be analyzed and designed based on intuitive design methods, physical understanding, quantitative performance evaluation using both hand calculation and simulation, and technology limitations.

Prerequisite: Grad. Standing

This course serves as an advanced course for electronics students in analog integrated circuits (IC) design. The course covers conventional and modern analog building blocks for analog signal processing in BJT and MOS technology both in continuous time and discrete time applications. The course includes analog multipliers, the op-amp applications in active filters, op-amp non-idealities, Nonlinearity cancellation of the MOS transistors, MOS-C Continuous time filters, Switched-C Circuits, and High frequency analog blocks ( ex: Current Conveyors and current feedback amplifiers).

Prerequisite: Grad. Standing

This course covers monotone and non-monotone transfer and driving-point characteristics of basic circuit elements, modeling techniques of electronic circuits containing nonlinear devices, autonomous and non-autonomous circuits, equilibrium points and stability analysis, the hysteresis phenomena and stiff systems, oscillators as nonlinear dynamical systems (harmonic and relaxation oscillators), state-space reconstruction. Static and dynamic trans-linear circuits, multipliers and other selected nonlinear circuits.

Prerequisite: Grad. Standing

This course discusses advanced and emerging topics selected from the area of Electronics. Contents of the course will be provided one semester before it is offered.

Prerequisite: Grad. Standing

This course includes introduction, background and biological inspiration. The course covers survey of fundamental methods of artificial neural networks: single and multi-layer networks; perceptions and back propagation. The course deals with associative memory and statistical networks, supervised and unsupervised learning, merits and limitations of neural networks, and applications.

Prerequisite: Grad. Standing

This course covers classification of discrete-time signals and systems. It covers basic and lattice structures, Finite-word length effects. This course includes Discrete Fourier Transform and its efficient implementations. The course deals with introduction to spectral analysis. It covers FIR and IIR filter design techniques: Windowing techniques, Analog-to-Digital transformation techniques, Computer-aided design techniques.

Prerequisite: Grad. Standing

This course covers Speech analysis, Digital processing of wave forms, Waveform coding, Parametric coding of speech: linear predictive coding, Text-to-Speech (TTS) synthesis, Stochastic modeling of speech signals, Pattern recognition and its application to speech, Speech recognition and its applications, Speaker recognition and its applications, emotion/talking condition recognition and its applications, and the latest developments in the different areas of speech.

Prerequisite: Grad. Standing

This course deals with Two-dimensional systems and mathematical preliminaries, Perception and human vision systems, Sampling and quantization, Image transforms, Image representation by stochastic models. The course covers Image data compression, enhancement, filtering, restoration. The course includes Reconstruction from projection and Analysis and computer vision.

Prerequisite: Grad. Standing

This course deals with advanced and emerging topics selected from the area of Signal and Image Processing. Contents of the course will be provided one semester before it is offered.

Prerequisite: Grad. Standing

This course covers the basics and research-related topics in power system protection. The course includes an introduction of power system protection including the zones of protection, primary and back up protection. It also covers protective devices such as Instrument transformers (Current transformers (CTs), voltage transformers (VTs)), electromechanical relays, tripping circuits and circuit breakers. Also, it sheds light on protection system types: Over-current protection, differential protection, and distance protection. The course also talks about the protection of power system equipment such as generator protection, bus-bar protection, transmission lines protection, and transformer protection. The course covers also some advanced topics such as protection coordination and digital protection.

Prerequisite: Grad. Standing

This course deals with the modeling and control of open-chain serial manipulator and their basic applications. Topics include an overview of robotic systems, serial manipulator, forward kinematic, inverse kinematics, Jacobian and forward velocity kinematics, inverse velocity kinematics, motion control and trajectory design.

Prerequisite: Grad. Standing

This course covers a review of Solar Resources and Photovoltaics systems. Maximum power point tracking (MPPT) algorithms for advanced PV systems. Inverter topologies for stand alone, utility/micro grids connected to advanced PV system. Simulation models and examples using Matlab Simulink. Smart grid technologies, including advanced metering infrastructure, demand side management. Case studies on energy storage system in smart grid.

This course covers basic integrated circuit design & process technology, Design of simple analog & digital IC components in Bipolar & MOS technology. Modeling & simulation of integrated circuits, SPICE simulation, Fundamentals of Photo-lithography, Basic integrated circuit layout techniques, Applications & types of IC chips.

The course includes: the convergence of wide-area wireless networking and mobile telephony to support ubiquitous access to information, anywhere, anyplace, and anytime. Topics include Mobile-IP, Ad-hoc networks, Local connectivity, 3G-wireless networks, Approaches to building mobile applications (e.g., mobile client/server, thin client, proxy architectures, and disconnected operation) and mobile e-commerce.

This course covers image formation, image representation and display, image processing (smoothing, enhancement, edge detection, filtering), convolution, Gaussian masks, scale, space and edge detection, Feature extraction, Hough transforms, stereoscopic vision and perspective projection, motion, active contour models.

This course includes introduction, background and biological inspiration. The course covers survey of fundamental methods of artificial neural networks: single and multi-layer networks; perceptions and back propagation. The course deals with associative memory and statistical networks, supervised and unsupervised learning, merits and limitations of neural networks, and applications.

This course covers basic integrated circuit design & process technology, Design of simple analog & digital IC components in Bipolar & MOS technology. Modeling & simulation of integrated circuits, SPICE simulation, Fundamentals of Photo-lithography, Basic integrated circuit layout techniques, Applications & types of IC chips.

The course serves as an advanced course for electronics students in analog integrated circuits (IC) design. The course will focus on conventional and modern analog building blocks for analog signal processing in BJT and MOS technology both in continuous time and discrete time applications. The course include analog multipliers, the op-amp applications in active filters, op-amp non-idealities, Nonlinearity cancellation of the MOS transistors, MOS-C Continuous time filters, Switched-C Circuits, and High frequency analog blocks ( ex: Current Conveyors and current feedback amplifiers).

The course reviews the main components of the VHDL, introduces the reconfigurable architecture such as FPGAs, explains how to use the IP cores to implement the reconfigurable Computing applications. In addition to reconfigurable case studies.

This is a first, graduate-level course in computer and communication networks. The course focuses on network mechanisms, such as error-control, routing, subnetting, congestion control, and resource allocation. The course covers also aspects of network protocols and technologies, such as Ethernet, WiFi, IP, TCP and UDP. Fundamental concepts of network delay and delay-bandwidth-product calculations will be covered. In addition, the general concept of packet switch architectures will also be covered.