ECTS - - Ph.D. Program in Electrical-Electronics Engineering

Compulsory Departmental Courses

Elective Courses

CE566 - Advanced Mathematical Methods in Civil Engineering (3 + 0) 5

First-, second- and higher-order linear ordinary differential equations, system of differential equations, power series solution of differential equations, Laplace transforms, partial differential equations, numerical integration and derivation, numerical solution of differential equations.

CMPE525 - Object-Oriented Design and Programming (3 + 0) 5

Thinking object-oriented, abstraction, object-oriented analysis and design concept, design patterns, UML: introduction, role of modeling, models and views, core diagrams, fundamental elements, sequence, class, and package diagrams, development lifecycle, Java and UML: Responsibility-Driven Design (RDD), and CRC, classes, messages, inheritance, sub

CMPE538 - Advanced Computer Networks (3 + 0) 5

Advanced concepts of TCP/IP computer networks, routing principles and routing algorithms in TCP/IP networks, wireless-networking, multimedia networks, network security, network management.

CMPE555 - Introduction to Recommender Systems (3 + 0) 5

Basic Concepts of recommender systems, collaborative filtering algorithms, content-based recommendation algorithms, knowledge-based recommendation algorithms, and hybrid recommendation algorithms, evaluating recommender systems, a case study to generate personalized recommendations.

CMPE564 - Natural Computing (3 + 0) 5

Problem solving by search, hill climbing, simulated annealing, artificial neural networks, genetic algorithms, swarm intelligence (including ant colony optimization and particle swarm optimization), artificial immune systems.

CMPE572 - Fundamentals of the Theory of Computation (3 + 0) 5

Models of computation, Church-Turing thesis, decidability and undecidability, recursive enumerability, time complexity, classes P and NP, space complexity, LOGSPACE, PSPACE-completeness.

EE503 - Linear System Theory (3 + 0) 5

Review of linear algebra concepts, linear system representations, existence of solutions, state transition matrices, canonical realizations, controller designs, observer designs, introduction to multi-input multi-output systems.

EE504 - Introduction to Systems Analysis (3 + 0) 5

Review of linear algebra concepts, classifications of systems and system representations, continuous and discrete time systems, state space realizations, analysis techniques: frequency domain, Laplace and z-domain analyses, solutions of linear systems, stability analysis; assessment of the techniques by a computational tool such as MATLAB.

EE505 - Neural Networks and Applications (3 + 0) 5

An introduction to basic neurobiology, the main neural network architectures and learning algorithms, and a number of neural network applications, McCulloch Pitts neurons, single-layer perceptrons, multi-layer perceptrons, radial basis function networks, committee machines, Kohonen self-organising maps, and learning vector quantization.

EE506 - Computational Methods in Electrical and Electronics Engineering (3 + 0) 5

Root finding and numerical integration, fixed and floating point arithmetic and error standards, one and multidimensional interpolation and extrapolation, numerical optimization techniques, least squares, statistical methods (Monte Carlo), computational approaches to linear transformations (Karhunen-Loeve, discrete Fourier).

EE519 - Speech Processing and Its Applications (3 + 0) 5

Features of the speech signal; time-domain and frequency-domain analysis techniques; speech coding fundamentals; speech processing applications, speech recognition, speech synthesis, speaker verification.

EE525 - Embedded System Design with Field Programmable Gate Arrays (3 + 0) 5

Language constructs of Verilog, behavioral models of combinational and sequential logic; logic, RTL, and high-level synthesis of combinational and sequential logic; datapath controllers; programmable logic and storage devices, HDL architectures for basic digital processing implementations.

EE543 - Communication Network Design (3 + 0) 5

Introduction to Petri nets and colored Petri nets; introduction to Omnet++; congestion management, throughput, task scheduling and resource allocation in communication networks; network architectures and topologies, OSI and TCP/IP reference models.

EE551 - Power Transmission Line Engineering (3 + 0) 5

Transmission line planning, overhead lines as system components, lightning protection, earthing, mechanical design, selection of conductors, insulators, overhead line fittings, conductor vibrations, foundations, sag and tension calculations, route selection, construction.

EE571 - Digital Signal Analysis (3 + 0) 5

Mathematical methods for signal processing, spectrum estimation, discrete Karhunen-Loeve transform, detection of a signal in noise, multiple signal classification (MUSIC), least mean square algorithm, classification systems, Kalman filters.

EE585 - Special Topics (3 + 0) 5

To be prepared by the instructor and approved by the departmental board.

EE606 - Special Topics (3 + 0) 5

Content of each special course will be announced prior to the term.

EE611 - Detection and Estimation (3 + 0) 5

Neyman-Pearson detector, hypothesis testing, maximum likelihood estimator, MAP, Kalman filtering, Wiener filtering, detection and estimation performance evaluation.

EE612 - Nonlinear Systems (3 + 0) 5

Nonlinear models and nonlinear phenomena, qualitative behaviour of second order systems, Lyapunov stability, passivity, Poincaré and Bendixon theorems, frequency response of nonlinear systems and describing functions, applications of Lyapunov theory, advanced nonlinear phenomena such as bifurcations.

EE621 - Computational Electromagnetics (3 + 0) 5

Finite difference time domain (FDTD), Finite Element (FE), geometric theory of diffraction (GTD) and method of moments (MoM) applied to antennas and scattering.

EE623 - Radar Cross Section Reduction Techniques (3 + 0) 5

Understanding of Radar Cross Section (RCS) analysis and RCS reduction, including formulation and implementation of several specific methods and enabling students to identify interesting and important research topics for Ph.D. work.

EE682 - Seminar (0 + 0) 5

Each PhD student is expected to give a presentation on his/her thesis work and attend the seminars conducted by other students and academic staff.

EE689 - Qualification Exam (0 + 0) 30

Topics covered in curriculum courses and related topics.

EE691 - Thesis Proposal (0 + 0) 20

Research topics covered in Electrical and Electronics Engineering.

EE697 - PhD Thesis (0 + 0) 150

Thesis topic as stated in the thesis protocol.

ISE501 - Foundations in IT Management (3 + 0) 5

Computing infrastructure overview; introduction to IT Services: event and fault management; problem management; change management; configuration management; asset management (inventory and software distribution); performance and capacity management;security management; network management; storage management; workload management; backup and recover

ISE502 - Organizational Management and Change (3 + 0) 5

Organizational behavior and management; personality and learning; perception, attribution and judgment of others; values, attitudes and work behavior, theories of work motivation, motivation in practice; groups and teamwork; leadership; communication; decision making, conflict and stress; organizational structure, change management principles: spon

ISE511 - IT Strategy Planning and Governance (3 + 0) 5

The IT strategic planning process; structuring the strategic planning process, analyzing the business environment; identifying the mission and competencies of your organization; assigning value and weight to enterprise objectives; reviewing established IT portfolios; measuring your IT governance maturity; aligning IT to your business objectives, de

ISE543 - Internet Security and Ethical Hacking (3 + 0) 5

Data encryption techniques and algorithms; public-key encryption, hash functions; digital signatures, authentication; network security; web security; system security, intruders, viruses, firewalls; the algorithms and data security tools; ethical hacking.

MDES600 - Research Methodology and Communication Skills (3 + 0) 5

Rigorous, scholarly research, particularly theses or dissertations. Literature review, surveys, meta-analysis, empirical research design, formulating research questions, theory building, qualitative and quantitative data collection and analysis methods, validity, reliability, triangulation, building evidences, writing research proposal

MDES610 - Mathematical Modeling via Differential and Difference Equations (3 + 0) 5

Differential equations and solutions, models of vertical motion, single-species population models, multiple-species population models, mechanical oscillators, modeling electric circuits, diffusion models, modeling by means of difference equations.

MDES615 - Analytical Probability Theory (3 + 0) 5

Sigma-algebra of sets, measure, integral with respect to measure; probability space; independent events and independent experiments; random variables and probability distributions; moments and numerical characteristics; random vectors and independent random variables; convergence of random variables; transform methods; sums of independent random v

MDES618 - Probabilistic Methods in Engineering (3 + 0) 5

Basic notions of probability theory, reliability theory, notion of a stochastic process, Poisson processes, Markov chains, statistical inference.

MDES620 - Numerical Solution of Differential Equations (3 + 0) 5

Numerical solution of initial value problems; Euler, multistep and Runge-Kutta methods; numerical solution of boundary value problems; shooting and finite difference methods; stability, convergence and accuracy; numerical solution of partial differential equations; finite difference methods for parabolic, hyperbolic and elliptic equations; explic

MDES621 - Numerical Linear Algebra (3 + 0) 5

Floating point computations, vector and matrix norms, direct methods for the solution of linear systems, least squares problems, eigenvalue problems, singular value decomposition, iterative methods for linear systems.

MDES631 - Engineering Decision and Risk Analysis (3 + 0) 5

Basic notions of probability, random variables, functions of random variables distributions, moments; first and second-order approximations; probability models for engineering analysis; Bernoulli sequence, binomial distribution, Poisson and related distributions, normal and related distributions, extreme-value distributions, other distributions us

MDES650 - Advanced System Simulation (3 + 0) 5

Discrete simulation models for complex systems, input probability distributions, random variable generation, statistical inferences, variance reduction, continuous processes, verification and validation, advanced models.

MDES654 - Decision Making Analysis (3 + 0) 5

Conflicting objectives in decision making; decision problems under certainty; utility theory for single-attribute and multi-attribute problems in decision analysis; individual versus group decisions.

MDES655 - Linear Optimization (3 + 0) 5

Sets of linear equations, linear feasibility and optimization, local and global optima, the Simplex method and its variants, theory of duality and the dual-Simplex method, network-Simplex algorithms, computational complexity issues and interior-point algorithms.

MDES672 - Advanced Topics in Digital Image Processing (3 + 0) 5

Review of image processing fundamentals, frequency and space domain image processing methods; wavelets, multiresolution processing, and orthogonal transforms; image and video compression standards; image segmentation and representation; nonlinear image processing methods.

MDES677 - Advanced Artificial Intelligence (3 + 0) 5

Intelligent agents, problem solving by searching, informed/uninformed search methods, exploration, constraint satisfaction problems, game playing, knowledge and reasoning: first-order logic, knowledge representation, learning, selected topics: evolutionary computing, multiagent systems, artificial neural networks, ant colony optimization.

ME601 - Advanced Mathematics for Engineers (3 + 0) 5

The objective of this course is to improve the skills of students in mathematics in advanced topic such as linear spaces and operators, matrix algebra, tensor fields, complex analysis and calculation of variations.

MECE521 - Control Engineering I (3 + 0) 5

State space analysis of systems, state feedback, observers, Lyapunov stability theory, phase portraits, and the describing function analysis.

MECE522 - Control Engineering II (3 + 0) 5

Fundamentals of state observers, regulator and control systems design, stochastic systems, Kalman filtering, MatLab-Simulink utilization; projects and laboratory studies about modeling and control of dynamical systems in mechatronic systems laboratory.

MECE531 - Advanced Dynamics (2 + 0) 5

The principles of Newtonian dynamics, planar kinematics and kinetics, three-dimensional kinematics, kinetics of rigid bodies, vibration.

PHYS502 - Electromagnetic Theory (3 + 0) 5

Vector analysis and vector algebra; electrostatics, the electric field, electric potential, conductors; potentials, Laplace?s Equation, method of images, multipole expansion; polarization; magnetostatics, magnetic vector potential, magnetic fields in matter; electrodynamics, Maxwell?s equations, conservation laws; electromagnetic waves, waves in

SE544 - Cognitive Aspects of Software Engineering (3 + 0) 5

Introduction to cognitive science and its methods; cognitive processes related to software engineering (memory, expertise, attention, decision making and problem solving, team cognition); basic experimental design; case studies on cognitive aspects of software engineering research.

SE546 - Decision Support in Health Informatics (3 + 0) 5

Choosing the correct information for different decisions and communicate its meanings to users; evaluation of statistical and other methods and tools; the difference between research databases and operational databases; techniques to effectively communicate quantitative healthcare data using tables and graphs; methods for choosing the right medium.

SE550 - Software Engineering (3 + 0) 5

Introduction to software engineering and related topics; software process and project metrics; project planning; scheduling and tracking; configuration management; software quality assurance; requirement analysis; data flow diagrams and related topics; design concepts and methods; implementation; testing methods and test strategies; object-oriented

SE558 - Software Architecture (3 + 0) 5

Introduction to software architecture; architecture business cycle; creating an architecture; introducing a case study; understanding and achieving quality; design, document and reconstruct software architecture; methods for architecture evaluation; quantitative approach to architecture design decision making; software product lines; middleware, mo

SE560 - Requirements Engineering (3 + 0) 5

Domain understanding and requirements eliciation; requirements evaluation; requirements specification and documentation; requirements quality assurance; requirements evolution; modeling system objectives with goal diagrams; risk analysis on goal models; modeling system agents and responsibilities; modeling system behaviours; integrating multiple sy

SE571 - Agile Software Development Approaches (2 + 2) 5

Introduction to agile methods; extreme programming (XP); Lean, Scrum; Crystal; feature-driven development (FDD); Kanban; dynamic systems development method (DSDM); architecture and design issues in agile software methods.

SE573 - Applied Machine Learning in Data Analytics (3 + 0) 5

Data statistics; linear discriminant analysis; decision trees; artificial neural networks; Bayesian learning; distance measures; instance-based and reinforcement learning; clustering; regression; support vector machines.