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Master of Science in Electrical and Electronics Engineering

College of Engineering
Electrical Engineering
Study System
Thesis and Courses
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 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 program learning outcome are to:

  1. Apply advanced theories and methodologies in the field of electrical and electronics engineering.
  2. Propose advanced engineering solutions with sustainability factors in global, economic, environmental, and societal context.
  3. Communicate effectively in oral and written forms to present complex and diverse problems to professional audience.
  4. Value the principles of professional ethics issues and develop fair and valid judgments in contemporary contexts.
  5. Function on multidisciplinary teams with management and leadership capabilities.
  6. Design and conduct experiments/simulation for research.
  7. Use advanced engineering tools to analyze and interpret data.

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 five different specializations areas of:

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 Engineering Department council and the approval of the college of engineering council, the Electrical  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
0402502/1502502 Optimization Methods in Engineering 3 Grad Standing
0402500/1502500 Applied Mathematics for Engineering 3 Grad Standing
0402501 /1502501
Engineering Research Methodologies  
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 Grad. Standing
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 1502540 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
0402575 Independent Studies in Electrical and Electronics Engineering
Grad. Standing
​Power System Protection
Grad. Standing
Grad. Standing
​Advanced Photovoltaics System in Smart Grids

Grad. Standing
​Reconfigurable Computing
Grad. Standing

Course Description

Applied Mathematics for Engineering (3-0:3)
This course covers solution of linear equations, Eigenvalue eigenvector decomposition, Special functions, Complex analysis, Fourier analysis, Laplace transform, Introduction to partial differential equations. The course deals with various examples from engineering disciplines.

0402501 /1502501 Engineering  Research Methodologies (3-0:3)
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.
0402502/1502502 Optimization Methods in Engineering (3-0:3)
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    ​

0402530 Linear Multivariable Control System (3-0:3)
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.

Nonlinear Systems Analysis and Design (3-0:3)
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.​

0402533 System Identification (3-0:3)
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 lo535op identification. Introduction to nonlinear system identification.
Special Topics in Control and Automation (3-0:3)
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 ​ ​

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

0402632 Predictive Control (3-0:3)
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.

0402536 Modeling and Control of Power Systems
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.

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.

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

0402538 Special Topics in Power Systems (3-0:3)
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.

Power System Protection
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.

Communication Systems Engineering (3-0:3)
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.

0402542 Detection and Estimation  (3-0:3)
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

0402543 Information Theory (3-0:3)
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.

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

Special Topics in Communications (3-0:3)
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.

1502540 Computer Networks (3-0:3)
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

Mobile Computing (3-0:3)
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.

0402550 Advanced Electronics (3-0:3)
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.​
Special Topics in Electronics  (3-0:3)
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.

0402554-1502550 Integrated Circuit Fundamentals (3-0:3)
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.

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

0402555 Non-linear Circuits Analysis and Design (3-0:3)
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.
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)
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.​

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

0402563 Speech Processing (3-0:3)
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.​

Image Processing and Applications (3-0:3)
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.

0402569 Special Topics in Signal and Image Processing (3-0:3)
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. 

0402660 Adaptive Filtering (3-0:3)
This course deals with adaptive signal processing. The course covers Fundamentals of adaptive filter theory. This course includes 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. The course deals with Applications to echo cancellation, equalization, noise canceling and prediction.

0402661 Wavelet and Time Frequency Signal Processing (3-0:3)
This course covers 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.

 Advanced Photovoltaics System in Smart Grids 
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.

(Cross listed with 1502534)
Neural Networks and Applications (3-0:3)
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. ​

(Cross listed with 1502631)
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.​

0402663 (Cross listed with 1502632)
Computer Vision (3-0:3)
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. ​ ​​

Reconfigurable Computing  (3-0:3)
The course reviews the main components of the VHDL, introduces the reconfigurable architecture such as FPGAs, and explains how to use the IP cores to implement the reconfigurable Computing applications. In addition to reconfigurable case studies. ​ 

0402575 Independent Studies in Electrical and Electronics Engineering (3-0:3)
In this course, students are expected to carry out an independent study on a current issue in a selected area of Electrical and/or 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 to be evaluated by the 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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