Course Descriptions

Linear System Theory
Dynamical system concepts. State-space representations. Linear and time-invariant systems: solution, impulse response, transfer functions. Controllability, observability, realizations. Discrete and sampled-data systems. State feedback. Observer design. Dynamical output feedback. Introduction to LQG optimal control.
Random Processes and Estimation Theory
Probability and random variables, averages, moments and characteristic functions, random sequences and convergence, important random processes, stationarity and ergodicity, linear systems with random inputs, power and higher order spectra, factorization and whitening, entropy and channel capacity. Hypothesis testing and decision, signal detection and estimation in noise, matched filter, parameter estimation, waveform estimation, linear estimation and optimum filtering, Kalman and Wiener filters.
Digital Design Automation
Today digital ICs are at the border of a billion transistors per chip. Such large chips can only be designed with the help of design automation tools. At such complexity, even software tools struggle even when running on GHz processors with GB’s of RAM. Hence, we have to develop clean-cut algorithms which are also efficient in run-time and memory use. This course lets the student understand the CS problems behind digital IC design automation tasks, offers algorithms, a chance to implement them as well as a look the EDA (Electronic Design Automation) sector.
Power System Analysis
Component of power systems, transmission lines, transformers, system modeling, network calculations, power-flow solutions and control, economic dispatch, fault analysis, system protection, and stability.
Power System Stability and Dynamics
Dynamic and transient stability of power systems, bifurcation and stability analysis with classical models, synchronous machine modeling using Park equations, multi-machine models of power systems, automatic voltage regulators, governors and stabilizers, low-frequency oscillations, sub-synchronous oscillations, and voltage collapse.
Power Generation
Introduction, engineering economics, thermodynamics and power plant cycle analysis, fossil fuels, coal and limestone handling, combustion processes, steam generators, circulation water systems, cycle performance impacts, power plant atmospheric emissions control, electrical systems, plant control systems, gas turbine, fluidized bed combustion, nuclear power, hydroelectric power, power plant planning and design.
Advanced Computer Methods for Power Systems
Data storage of power systems, construction of bus admittance and bus impedance matrices, sparsity programming, triangular factorization, power-flow studies, programming for power-flow of a real power system, programming for economic generation dispatch.
Speech Processing
Speech production and representation, digital signal processing, random processes, short-time Fourier analysis, Cepstral processing, linear predictive coding, speech recognition, hidden Markov models, acoustic and language modeling, speech and audio compression, text-to-speech synthesis.
Computer Vision and Pattern Recognition
Hypothesis testing and Bayesian decision, feature extraction, geometry descriptions and transforms, parameter estimation and supervised learning, unsupervised learning and clustering, non-parametric estimation, linear discriminant functions, expectation-maximization techniques, hidden Markov models.
Introduction to Information and Coding Theory
Entropy and its properties, joint and conditional entropy, source coding, Kraft inequality, optimum and maximum likelihood decoding, Huffman coding, Lempel-Ziv coding, channels and channel capacity, linear block codes, error detection and correction, syndrome decoders and parity check theorem, bit error rate, cyclic codes, convolutional codes, the Viterbi algorithm.
The purpose of this seminar is to equip the student enrolled in a program with a thesis with the necessary background for preparing a thesis. Although not compulsory, it is expected that the student prepares a pre-research document on her/his thesis subject and make a presentation at the end of the term.
Master Thesis
The Master Thesis is a study that students enrolled in a program with a thesis have to carry out under the leadership of an advisor on a subject related to the program followed. The thesis has to be prepared in line with academic ethic rules, presented to and approved by a thesis committee. The student has to register to this course for at least two terms.