Electrical Engineering

This course covers working principles and models of basic circuit components such as resistor, capacitor, inductor, diode, and transistor. Students learn to analyze the complex electric circuit problems composed of multiple circuit components using abstractions and various mathematical methods and gain an understanding of the working principles of various logic, memory, and amplifier circuits. The course provides students the ability to understand/modify/write LabView code that can be used to test electric circuits. Topics include Network analysis, Node voltage, Mesh current, Superposition, Impedance, RLC circuit, Diode, MOSFET, Amplifier, Logic and memory devices, Bipolar junction transistor (BJT), BJT small signal model, Lab work via LabView. 

This course provides general knowledge in radio frequency applications, especially those which are common in radio communications. The fundamentals are introduced without penetrating the electronics or design details. The different parts are treated as functional blocks defined by their physical properties. This gives a basic understanding of the radio receiver or the cellular phone but also the requirements put on the used circuits. Thus, this is a compulsory course for those who later want to specialize as radio frequency designers.

This course covers an overview of solid-state microanalysis methods, including elastic and inelastic scattering, identification of phases by morphology, chemical composition, electron diffraction, and microscopy. Principles and functions of different types of microscopes for materials analysis as well as spectroscopy for elemental analysis, analysis of spectra are also reviewed. Methods for surface analysis: Atomic force microscopy, scanning tunnelling microscopy, LEED, X-ray photoelectron spectroscopy (XPS) are covered.

This course introduces the fundamental properties and characteristics of solid-state materials and structures used in modern semiconductor devices and integrated circuit (IC) technologies. 

Topics include Solid-State Electronics and applications, Crystal structure of solids, Introduction to quantum mechanics, Introduction to the quantum theory of solids, Semiconductor in equilibrium, Carrier transport phenomena, Excess carriers in semiconductors, The pn junction. 

The course deals with time discrete signals and systems. Items such as the Fourier Transform, the Discrete Fourier Transform (DFT) and the z-transformed are treated in the course as well as some basic structures for implementation of digital filters. Also, system function and frequency functions are introduced as well as digital filters. Digital processing of analogue signals using A/D and D/A conversion is studied. In the laboratory work, practical applications of digital signal processing such as speech signals processing and biomedical signals processing are treated. Also, the course includes basic filter design using Matlab and digital signal processors (DSP).

Systems do not in general naturally behave in a manner which accords with the user’s wishes. Systems must in general be extended by the addition of a controller in order to force them to behave in an acceptable fashion. The controller may be a human (as in the case of the driver of a car for example), but the controller may also be a human-designed engineering system in its own right. In the latter case the controller is called an automatic controller. This course addresses the need for, the value of and the design of automatic controllers for some of the most common classes of engineering systems. Automatic controllers appear in more or less every engineering environment, from automotive/aerospace to biomedical equipment and including almost everything in between.

This course covers the nature of digital logic and numbering systems. Topics include: Basic gates, Boolean algebra, Karnaugh maps, memory elements, latches, flip-flops, design of combinational and sequential circuits, integrated circuits and logic families, shift registers, counters, multiplexers, demultiplexers, decoders, encoders, and parity circuits, Number systems, 1’s and 2’s complements, arithmetic circuits, fixed-point and floating-point representations, memory types, design of circuits using ROMs and PLAs. The course involves exposure to logic design automation software and an introduction to FPGAs and HDL. Prerequisite: fundamentals of computing. 

This is the laboratory component and corequisite of the DIGITAL LOGIC DESIGN (host institution course number ECNG 2101) course. It covers experiments in digital design and experiments illustrating material of the main course including an FPGA-based project.

This course provides the basic tools required for understanding linear systems, and the effect that such systems have on deterministic signals. The course covers linear time-invariant systems in terms of input-output relationships, using both time and frequency domain methods and includes concepts related to signal representation, linear convolution, Fourier analysis, sampling of continuous-time signals, and Laplace transforms.

This course covers the mathematical fundamentals of probability theory and complex variables which are necessary in the study of integrated circuits, communications, communication networks, control systems, signal processing, energy and new media. There is a strong emphasis on the application of these concepts to electrical and computer engineering problems, such as the Gaussian distribution in communications, random variable distributions for system reliability, complex random variables. This course requires students to take prerequisites.