Özyeğin University, Çekmeköy Campus Nişantepe District, Orman Street, 34794 Çekmeköy - İSTANBUL

Phone : +90 (216) 564 90 00

Fax : +90 (216) 564 99 99

E-mail: info@ozyegin.edu.tr

Electrical and Electronics Engineering Courses

Electrical and Electronics Engineering Courses

EE 501 Linear Systems

The students will learn the principles of continuous or discrete-time linear systems, simple estimation with and control of linear systems and analysis of dynamic linear systems with inputs and outputs. Topics include QR factorization, least squares, least norm, their applications, analysis of autonomous linear systems and systems with inputs and outputs.
 
EE 503 Stochastic Processes

The students will learn the principles of probability, random variables, and stochastic processes. Topics include principles of probability, random variables, expectation, maximum likelihood and maximum a-posteriori probability detection, minimum mean square error estimation, convergence and limit theorems, random processes, Markov chains, and queuing theory.

EE 519 New Display Technologies

This course aims to describe principles for designing color displays, the classification and specifications of display technologies, basic operational principles of main electronic devices used in displays and fundamental physics and sciences behind display technologies. Topics include fundamentals of optics for displays, human vision and photometry, thin-film transistors, liquid crystal displays, inorganic light-emitting diode (LED) displays, organic light-emitting diode (OLEDs) displays, plasma displays, field emission displays, paper-like and low power displays, mobile displays, microdisplays, and projection displays.
 
EE 520 Advanced Digital Signal Processing

This course will introduce the graduate level statistical signal processing and modeling techniques, time-frequency representations and practical applications of advanced signal processing techniques. The course will review discrete-time signal processing and random processes. Various deterministic and stochastic signal modeling methods such as Padé, Prony, autoregressive (AR), moving average (MA) and ARMA methods will be introduced. Then, optimum linear filters, FIR and IIR Wiener filters and discrete Kalman filters will be presented. Next, the estimation techniques for the power spectrum of random processes will be introduced which include periodogram based nonparametric methods and parametric methods. Furthermore, frequencies of harmonics processes are estimated by using methods such as Pisarenko and MUSIC. Next, design and implementation of adaptive filters focusing on LMS and recursive least squares algorithms are discussed. In addition to the advanced statistical signal processing methods, time-frequency signal representations such as short-time Fourier Transform and wavelet transform will be reviewed by including the discussion of Fractional Fourier Transform and Wigner distribution. Finally the applications of advanced signal processing techniques in modern technologies will be discussed such as speech & image processing, spectrum sensing, array processing, communications systems, compressed sensing systems. The methods and analyzes are implemented with an advanced set of practical algorithms mainly in MATLAB leading to developing advanced techniques for the solution of signal processing problems. 

EE 521 Digital Image Processing

Topics include color theory and human visual system, multi-dimensional sampling and Fourier analysis, image transforms, enhancement, noise filtering, restoration, segmentation, and reconstruction of images, as well as image coding.

EE 522 Digital Speech Processing

Topics include speech signal analysis, speech coding, text-to-speech synthesis, speech recognition, and voice authentication techniques.

EE 523 Detection and Estimation Theory

Major topics include simple hypothesis testing, composite hypothesis testing, Bayesian test, Neyman-Pearson test, detection of deterministic or random signals in noise, detection of signals with unknown parameters, criteria for optimal estimation, Cramer-Rao bounds for estimator performance, deterministic parameter estimation, random parameter estimation based on the Bayesian approach.

EE 525 Machine Learning

Topics include linear regression and classification concepts and techniques, classification using neural networks, Gaussian mixture models and Expectation Maximization algorithm, principal component and factor analysis, support vector machines and multi-classifier methods.

EE 526 Digital Video Processing

Topics include video capture and display systems, spatio-temporal sampling and Fourier analysis, enhancement, noise filtering, restoration, motion segmentation, and super-resolution reconstruction of video, as well as video coding.

EE 528 Video Compression

Topics include entropy coding, scalar and vector quantization, bit allocation, predictive coding, transform coding, subband coding, and world standards for video compression.

EE 533 Computer Vision

Topics include cameras and projections, feature detection and matching, stereo vision and multiple view geometry, motion and depth estimation, structure from motion and object tracking.

EE 534 Advanced Object-Oriented Programming

Course topics include object-oriented programming language concepts, design patterns and idioms, architectural patterns, and parallel programming patterns. A brief introduction to UML, generics (templates), aspect-oriented programming, and feature-oriented programming will also be made.

EE 541 Information Theory

This course offers an introduction to the theory of information and its applications to reliable, efficient communication systems. Topics include mathematical definition and properties of information, source coding theorem, lossless compression of data, optimal lossless coding, noisy communication channels, channel coding theorem, the source channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, and time-varying channels.

EE 544 Wireless Communication

This course provides a basic understanding of the underlying mechanisms in wireless communication systems. Topics include optimum detection of digital signals in additive white Gaussian channels, wireless channel propagation, digital modulation, performance analysis of wireless systems, diversity techniques, multiple antennas and space-time communications, multi carrier modulation, spread spectrum, multi -user systems and an overview of wireless networks. 

EE 551 Wireless Communication Technologies

This course will present the fundamental concepts of wireless communication technologies and their applications in communication systems by pointing out the future research aspects.  Radio wave propagation models and wireless channels with their unique characteristics such as path loss, shadowing and fading will be presented. The wireless channel capacity will be studied by using the fundamental information theoretical results.  Fundamental modulation techniques including amplitude, phase and frequency modulation will be covered. Error and outage probability performances of digital modulation techniques over wireless channels will be studied.  Transmitter and receiver diversity techniques, adaptive transmission and modulation, equalization, multicarrier and spread spectrum techniques will be presented for performance improvements in wireless channels. 
Furthermore, innovative and important applications of wireless communication technologies such as sensor networks, communication technologies for smart homes and vehicular applications will be studied.

EE 562 Digital Electronics and FPGA Design

Topics include: CMOS digital circuit design, fundamental VLSI concepts, board level digital electronics, ASIC vs FPGA vs CPU, HDL vs Schematic, Verilog language, Data Flow Graphs, RTL design, timing optimization, area optimization, synthesis, verification, capturing functional and timing specs from a loose design problem, deciding if an FPGA is the right choice, designing electronic systems around FPGAs, lab work on specific designs such as Calculator, Seven Segment driver, Mouse driver, VGA driver, a simple CPU. In the process of taking this course, describe how digital circuits are implemented, Data Flow Graphs, Timing Constraints, Speed-Area-Power trade-offs as well as the trade-off between using FPGAs and regular CPUs.

EE 564 Computer Architecture and Performance

This course has 3 parts:
1. Computer Architecture: 
In this part, we will cover fundamentals of modern day CPUs. Such an understanding is very useful even for software professionals, especially when they write timing-critical and/or performance optimized code. Some headings from the architecture part of the course will be: MCUs vs uPs vs DSPs, Pipelining in processors and elsewhere, RISC vs CISC, Superscalar vs VLIW, Branch Prediction, Memory Hierarchy and Caching Policies, MMU, System Buses and DMA.
2. Computer Arithmetic:
Starting with the ALUs in CPUs, we will move into Computer Arithmetic. Some headings from the arithmetic part of the course will be: Fast Adders, Column Compression and Fast Multipliers, Priority Encoders and Arbitration Circuitry (which is also used in network switching equipment).
3. Sequential and GPU based Programming for High Performance:
We will show how we can utilize our computer architecture knowledge to rewrite code to boost performance. We will also go into programming of special architectures such as GPUs.
The course also has a PROJECT. Each student will have a choice between 5 different project types:
1. Simulation of a processor architectural feature in a high-level language (e.g., C, Java, Perl) to compare performance yield of different strategies/policies (e.g., caching policies, branch prediction methods).
2. Design of a simple processor on an FPGA board using Verilog or VHDL. (Students that are interested in this, but do not have a Verilog or VHDL background, will be able to get extra lecturing and lab help from me and my graduate students.)
3. Design of cutting-edge Computer Arithmetic algorithms for fast ALU operations. This project will involve writing a Verilog or VHDL generator in a high-level language and demonstrating an instance of a generated circuit on an FPGA board.
4. Writing a timing-critical software on an MCU board (e.g., PIC) interfacing to a VGA Monitor (e.g., Pong Game).
5. Acceleration of an application on GPUs.
 
EE 565 Embedded System Design

Topics include top-down system design, MCUs, uPs, DSPs, RISC architecture, branch prediction, caching, MMU, system buses, DMA, superscalar, VLIW, PIC, ICD, interrupt handling, PIC development platforms, timers, peripherals, OS fundamentals, semaphores, file systems, embedded Linux, ARM- based systems, HW/SW resource management, parallel programming for embedded computing.

EE 566 System on Chip Design

Topics include: taxonomy of FPGA, ASIC, SoC; digital logic design review; design flows; Verilog language overview; testbench writing and simulation; synthesis; basic design examples on an FPGA board; more advanced designs; SoC design example; chip design for video applications.

EE 567 Optics and Optical Methods in Engineering Science

This course introduces basic concepts of optical engineering. The course will start with fundamentals of ray optics and continue with electromagnetic wave propagation and solution to the wave equation. Travelling and standing waves will be discussed. Simple harmonic oscillator, free and forced oscillations will be studied. Reflection, refraction, interference and polarization of waves will be presented. Applications of optical techniques such as interferometry, holography will be studied. An introduction to lasers and their applications in various engineering fields will be given. Basic theory of cavity and characteristics of various lasers will be presented. The course will also cover basic concepts on the design of optical instrument components such as lenses, optical sensors, polarizers and beam expanders.

EE 568 Hardware Design Patterns

This course is about abstracting out hardware modules into templates similar to software design patterns, and turning them into clean, application agnostic, reusable modules. 

EE 571 Energy Efficient Solid State Lighting Systems

In this course, fundamentals of lighting systems, electronics, optical design concepts, materials and applications of SSL are studied. Students will also design an SSL system and they will utilize thermal and optical tools to design the SSL lamp ın the term project.

EE 578 MEMS Devices and Applications

This course teaches MEMS devices and their applications. The course starts with MEMS fabrication techniques. Then MEMS sensors and actuators along with working principles of these devices will be discussed. Also, applications of MEMS devices will be presented. 

EE 581 Microwave Engineering I

Topics include the theory of transmission lines, equivalent circuits, waveguides, planar transmission lines (microstrip, stripline), characteristic impedance, maximum power transfer, the Smith chart, impedance matching, equivalent circuits, microwave network parameters with emphasis on S-parameters, signal flow graphs, power dividers and couplers.

EE 582 Microwave Engineering II

Topics include filters, resonators, active microwave circuits such as low-noise amplifiers, mixers, oscillators, noise, microwave system analysis and fundamentals of antennas such as gain, radiation pattern, radiation resistance, etc.

EE 585 Quantum Mechanics for Engineers

Quantum mechanics has recently become increasingly important for a wide range of disciplines such as electrical and mechanical engineering, material science and nanotechnology. This course introduces quantum mechanics to engineers. The level of required background in physics and mathematics has been kept minimum to suit the students from diverse engineering disciplines. The core material on Schrodinger’s equation and on the mathematics behind quantum mechanics will be explained. The approximation methods of quantum mechanics will be presented. Methods for one-dimensional problems, spin and identical particles will be explained. 

EE 588 Photonics

This is an introductory level photonics course and it explains the fundamentals of photonic processes and devices. It has a wide range of applications to devices and systems used in modern lighting, information and telecommunications technologies. In this course we will start with the discussion on the interaction between photons and atoms. We will discuss lasers and semiconductor based photonics devices. We will present acousto-optics, electro-optics, nonlinear optics, ultrafast optics, interconnects and switches.
 
EE 592 Nonlinear Optimization

The course covers the key concepts, models and solution approaches in local and global nonlinear optimization. Local optimization topics include convex sets and functions, local optimality conditions, duality, Lagrange multipliers, unconstrained and constrained optimization methods. 
Global optimization topics include concave, difference of convex (DC), continuous and Lipschitz optimization models, and a review of the most prominent global solution strategies.
The main emphasis is placed on the modelling and algorithmic aspects of nonlinear optimization, including also the use of software packages to solve various NLO models.
Course attendees will learn the fundamental theoretical concepts, and will also gain insight into the applications of nonlinear programming in engineering and the sciences.

EE 593 Power Electronics

This course in power electronics covers conversion techniques of electrical power ranging from milliwatts to megawatts applications.

EE 594 Switching Power Supplies

Switching power supplies are power electronic circuits that perform
power conversion by operating a semiconductor switch in on-off mode at high frequencies. Because of having low loss elements (capacitor,
inductor, transformer, semiconductor switch), high efficiency, low weight and small size make these supplies to be wide spread used in today's many applications. The aim of this course is to give mathematical tools for steady-state and dynamic analysis of these supplies. The necessary tools required in the design of switching power supply such as magnetic elements and controllers are also within the scope of this course.
 
EE 595 Power Management for Advanced Energy Storage Systems

This course will introduce the graduate level analysis of energy storage devices and their modeling approaches. The power management  for power system is covered in detail. Demand and generation side characteristics are introduced. Management of power resources for effective use of energy is explained.  From the economic and technical point of view their order in use is given. The battery types are explained and modeling approach is given. State of charge estimation is modeled and its application in microcontroller. The power electronics and static energy conversion (based on power electronics) is explained: AC to DC, DC to DC and DC to AC converters are thought with some circuit configurations in power management systems.

EE 596 EMC Engineering

This course focuses on basic and general EMC science. General EM concept will be given to students firstly. Students will be encouraged for good EMC design techniques. They will develop ability to diagnose and solve EMC problems. By the way, students will learn the reasons of EMC problems and be able to solve these problems during tests. They will review available tools and methods that help to design EMC compliant products. The standards related to EMC tests will be overviewed during lessons.  The covered topic includes antenna modeling and simulation.

EE 670 MsC Term Project

EE 680 Seminar

EE 690 MsC Thesis

EE 990 PhD Thesis

EE 901/902/903 Fundamental Research I / II / III

Topics include assessment and detailed description of an open research problem, conducting an exhaustive literature survey on the topic, developing a solution to this problem using a novel technique and formulating an experimental, theoretical and/or simulation platform to assess the performance of the developed solution.