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Master of Science in Electrical and Electronics Engineering

College of Engineering
Electrical Engineering
Study System
Total Credit Hours
33 Cr.Hrs
2-4 Years
Fall & Spring
Sharjah Main Campus
Study Mode
Full Time and Part Time

Master of Science in Electrical and Electronics Engineering

The Electrical and Computer Engineering Department at the University of Sharjah has developed a Master of Science program in Electrical and Electronics Engineering that will prepare its graduates to confidently confront the challenges of the information technology revolution and prepare them for highly rewarding careers by providing advanced knowledge and skills. The Department aspires to have well-recognized engineering programs involving excellence in teaching and research.

The overall objective of the Master of Science in Electrical and Electronics Engineering is to strengthen the academic and professional knowledge of its students. The program is also intended to provide students with depth in their chosen area of focus. The specific objectives of the program are to:

  1. Educate graduate students with the advanced knowledge and skills required to solve research oriented technical problems in electrical and electronics engineering.
  2. Provide graduate students with an advanced grasp of theories and the insight required to enhance their professional careers and/or to pursue further higher education and lifelong learning.
  3. Fulfill the future needs of the Research and Development (R&D) for various industries and establishments of the United Arab Emirates (UAE) and the region as a whole.
  4. Promote a sense of leadership with emphasis on scholarship and professional ethics.

Program Structure
Program Components

The program requirements for the MSEEE program comprise of 9 credits of basic courses (3 courses) required of all students and 15 credits of elective courses (5 courses) in four different specializations areas of:

Control and Power
Communication Systems
Signal and Image Processing

So, to be awarded the MSEEE degree, a student has to complete 33 credit hours distributed as given in Table 1.

After careful reading the external review team (ERT) report and in corresponding to the requirement no. 8 and requirement no.13 and after taking the approval of the Electrical and Computer Engineering Department council and the approval of the college of engineering council, the Electrical and computer engineering department modified and shortlisted the list of courses as shown below.

Table 1 - Program Components

Requirements Credits
3 Basic Courses 9
5 Elective Courses 15
Thesis 9
Total 33

I. Basic Courses

Table 2 - MEE Portfolio of Basic Courses

Department Requirements – Basic Courses
Course No. Course Title Credits Prerequisite
0402502/0403502 Optimization Methods in Engineering 3 Grad Standing
0402500/0403500 Applied Mathematics for Engineering 3 Grad Standing
0402501 /0403501
Engineering Research Methodologies  Engineering 3 Grad Standing

II. Elective Courses

Table 3 – MEE Portfolio of Elective Courses

Index Course No. Course Title Pre-requisite
1 0402530 Linear Multivariable Control System Grad. Standing
2 0402532 Nonlinear Systems Analysis and Design 0402530
3 0402533 System Identification Grad. Standing
4 0402539 Special Topics in Control and Automation Grad. Standing
5 0402630 Robust Feedback Control 0402530
6 0402632 Predictive Control 0402530
7 0402536 Modeling and Control of Power Systems Grad. Standing
8 0402537 Analysis and Control of Electrical Machines Grad. Standing
9 0402538 Special Topics in Power Systems Grad. Standing
10 0402552 Advanced Power Electronics Grad. Standing
11 0402540 Communication Systems Engineering Grad. Standing
12 0402542 Detection and Estimation 0402540
13 0402543 Information Theory Grad. Standing
14 0402544 Error Control Codes Grad. Standing
15 0402549 Special Topics in Communications Grad. Standing
16 0402643

Mobile Computing Grad. Standing
17 0403540 Computer Networks Grad. Standing
18 0402550 Advanced Electronics Grad. Standing
19 0402551

Analog IC Design Grad. Standing
20 0402554

Integrated Circuit Fundamentals Grad. Standing
21 0402555 Non-linear Circuits Analysis and Design Grad. Standing
22 0402653 Advanced Optoelectronics Grad. Standing
23 0402559 Special Topics in Electronics Grad. Standing
24 0402535

Neural Networks and Applications Grad. Standing
25 0402560 Digital Signal Processing Grad. Standing
26 0402562 Pattern Recognition Grad. Standing
27 0402563 Speech Processing Grad. Standing
28 0402564 Image Processing and Applications 0402560
29 0402569 Special Topics in Signal and Image Processing Grad. Standing
30 0402660 Adaptive Filtering 0402560
31 0402661 Wavelet and Time Frequency Signal Processing 0402560
32 0402663

Computer Vision Grad. Standing
33 0402575 Independent Studies in Electrical and Electronics Engineering Grad. Standing

Course Description


0402502/0403502 Optimization Methods in Engineering (3-0:3)
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. ​ ​

Applied Mathematics for Engineering (3-0:3)
Solution of linear equations. Eigenvalue eigenvector decomposition. Special functions. Complex analysis. Fourier analysis. Laplace transform. Introduction to partial differential equations. Various examples from engineering disciplines. ​ ​

0402501 /0403501 Engineering  Research Methodologies (3-0:3)
Overview of methodological approaches to research; Basics of research design (e.g., hypothesis formulation); The research process: documenting research, sources of information, research funding, creativity and intellectual discovery; Guidelines and a framework for efficient development of research; legal and ethical issues; protecting and exploiting research; Intellectual Property rights; Managing a research project: supervision, planning and organization; problems and pitfalls. ​ ​

Nonlinear Systems Analysis and Design (3-0:3)
Introduction to nonlinear systems dynamics. 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. Chaos. ​ ​

0402533 System Identification (3-0:3)
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. ​ ​

0402536 Modeling and Control of Power Systems (3-0:3)
Dynamic model of synchronous machines. Excitation and governor systems. Nonlinear and linear modeling of single machines infinite bus systems. Stability analysis and control design. Direct method of stability determination. Multi-machine systems modeling. Power system dynamic equivalents ​ ​

0402537 Analysis and Control of Electrical Machines (3-0:3)
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. ​ ​

Special Topics in Control and Automation (3-0:3)
Advanced and emerging topics are selected from the area of Control and Automation. Contents of the course will be provided one semester before it is offered ​ ​

0402630 Robust Feedback Control (3-0:3)
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. ​ ​

0402632 Predictive Control (3-0:3)
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. ​ ​

0402552 Advanced Power Electronics (3-0:3)
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 ​ ​

0402538 Special Topics in Power Systems (3-0:3)
This course gives a glimpse for several attractive topics for research in power systems along with their subsystems. The course covers Flexible AC Transmission Systems, (FACTS), controllers and how these controllers are operated to improve transient stability, and control the active and reactive power in the transmission systems. The course also presents the power quality concepts, problems and phenomena along with their detection and mitigation means and tools. Finally, the course provides information for recent distributed generation systems and their integration with the power grids. ​ ​

0402530 Linear Multivariable Control System (3-0:3)
State space representation of systems. Linear algebra background.  Modeling of multivariable systems.  Realization theory.  Controllability and observability. Minimality. Stability.  State feedback and Estimation. Separation theorem. Output Feedback. Compensation. ​ ​

Communication Systems Engineering (3-0:3)
Representation of signals. Spectral density and autocorrelation. PAM and PCM systems.

Detection of binary and Mary signals in Gaussian noise. Matched filter and correlator receivers. Pulse shaping. Band pass modulation and demodulation techniques. Error performance for binary and Mary systems. Spectral analysis of digital signals.

Communication link analysis. ​ ​

0402542 Detection and Estimation  (3-0:3)
Binary and M-hypotheses Detection techniques: Maximum likelihood, Newman Pearson, Minimum probability error, Maximum a posteriori probability, Bayes decision and mini-max detection. Parameter estimation: weighted least squares, BLUE, Maximum likelihood, Mean square estimation. Signal estimation and filtering: Wiener filtering, Kalman filtering and estimation. Simultaneous detection and estimation. Application to system identification and communication systems. ​ ​

0402543 Information Theory (3-0:3)
Measures of information, Entropy, Source Coding theory, Lossless data compression, Huffman

Codes, Ziv-Lempel and Elias Codes, Arithmetic Codes, Run-length Encoding, Sources with memory, Lossy data compression, Rate distortion theory, Mutual Information, Memoryless, channels, Channel capacity, Channel coding theory, Differential Entropy, Capacity of AWGN channels. ​ ​

0402544 Error Control Codes (3-0:3)
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. ​ ​

Special Topics in Communications (3-0:3)
Advanced and emerging topics are selected from the area of communications. Contents of the course will be provided one semester before it is offered. ​ ​

0403540 Computer Networks (3-0:3)
Network technologies, Packet switching, Cell switching, Switching and routing, Packet switch architectures, Internet routers, Network interface, Protocol processing, Network control, Traffic management, Congestion control. ​ ​

0403640 Mobile Computing (3-0:3)
The course discusses 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. ​ ​

0402550 Advanced Electronics (3-0:3)
The Advanced electronics will cover high frequency circuits with special attentions to integrated circuits at both transistor and system levels. The course include 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. ​ ​

0403550 Integrated Circuit Fundamentals (3-0:3)
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. ​ ​

0402551 Analog IC Design (3-0:3)
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). ​ ​

0402555 Non-linear Circuits Analysis and Design (3-0:3)
This course is an advanced course in electronics aiming at studying nonlinear modeling and analysis techniques for nonlinear circuits as well as their applications. Topics that are covered include, equilibrium points, stability analysis, nonlinear driving point characteristics, hysteresis, nonlinear differential equation models, nonlinear transistor models, sinusoidal and relaxation oscillator's analysis and design, analog multipliers, introduction to nonlinear dynamics and chaos. ​ ​

0402653 Advanced Optoelectronics (3-0:3)
The course serves as an advanced course for optoelectronics course of undergraduate students. The course topics include variety of different subjects related to the physics and operating characteristics of optoelectronic semiconductor devices. This include a detail discussion of the design and operation of optical LEDs, the basic physics and operation of lasers and photodetectors, details of the basic physics and operation of solar cells, the design and operation of optoelectronic modulation and switching devices, and design of optoelectronic integrated circuits. ​ ​

0402560 Digital Signal Processing (3-0:3)
Classification of discrete-time signals and systems. Basic and lattice structures, Finite-word length effects. Discrete Fourier Transform and its efficient implementations. Introduction to spectral analysis. FIR and IIR filter design techniques: Windowing techniques, Analog-to-Digital transformation techniques, Computer-aided design techniques. ​ ​

0402562 Pattern Recognition (3-0:3)
Decision functions. Distance classification. Clustering algorithms. Pattern classification by likelihood, Deterministic pattern classifier, Supervised and unsupervised classification, Statistical pattern classifier. Feature selection. Neural network approach to pattern recognition. Applications to engineering and machine vision. ​ ​

0402563 Speech Processing (3-0:3)
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. ​ ​

Image Processing and Applications (3-0:3)
Two-dimensional systems and mathematical preliminaries. Perception and human vision systems. Sampling and quantization. Image transforms. Image representation by stochastic models. Image data compression, enhancement, filtering, and restoration. Reconstruction from projection. Analysis and computer vision. ​ ​

0402569 Special Topics in Signal and Image Processing (3-0:3)
Advanced and emerging topics are selected from the area of Signal and Image Processing. Contents of the course will be provided one semester before it is offered. ​ ​

0402660 Adaptive Filtering (3-0:3)
Introduction to adaptive signal processing.  Fundamentals of adaptive filter theory.  The LMS algorithm, LMS-based algorithms.  Conventional RLS adaptive filtering.  Adaptive lattice-based RLS algorithms.  Fast algorithms.  Implementation issues.  Adaptive IIR filters.  HOS-based adaptive filtering.  Introduction to nonlinear filtering.  Applications to echo cancellation, equalization, noise canceling and prediction. ​ ​

0402661 Wavelet and Time Frequency Signal Processing (3-0:3)
Cosine transform and short-time Fourier transform, Analysis of filter banks and wavelets, Sub-band and wavelet coding, Multirate signal processing, Wavelet transform, Daubechies wavelets, Orthogonal and biorthogonal wavelets, Time-frequency and time-scale analysis, Design methods, Applications of wavelets to audio and image compression, Medical imaging, Geophysics, Scientific Visualization. ​ ​

0402535 (Cross listed with 0403534)
Neural Networks and Applications (3-0:3)
Introduction, background and biological inspiration. Survey of fundamental methods of artificial neural networks: single and multi-layer networks; Perceptions and back propagation. Associative memory and statistical networks. Supervised and unsupervised learning. Merits and limitations of neural networks. Applications. ​ ​

0402663 (Cross listed with 0403632)
Computer Vision (3-0:3)
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. ​ ​

0402575 Independent Studies in Electrical and Electronics Engineering (3-0:3)
The student is expected to carry out an independent study on a current issue in a selected area of Electrical-Electronics Engineering. This study is to be supervised by a faculty member and requires the approval of the department. The student is required to produce a formal report, which will be evaluated by his instructor. ​ ​

0402590 Graduate Seminar (3-0:3)
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. ​ ​

0402599 Master Thesis (3-0:3)
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. ​ ​

Special Admission Requirements
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