Signal Theory (EESC 6350), Fall 2018
Basic overview of matrix and vector analysis, vector representation of
signals, least squares (LS) approximation and the orthogonality
principle, Minimum-norm and MNLS solutions, psuedo-inverses, eigen-value
and singluar-value decompositions. Time permitting, additional advanced
topics will also be visited.
Probability and Statistics (ENGR 3341), Spring 2018
Probability axioms, conditioning and independence, combinatorics, random
variables and distributions, averages and moments, functions of a random
variable, joint distributions and densities, limits, moment generating
function, the central limit theorem, sample mean and variance,
regression techniques, empirical distributions, law of large numbers.
Theory (EESC 6344), Fall 2017
Theory and practice of error-control coding; Linear block codes,
cyclic codes, BCH codes, Reed-Solomon codes, convolutional codes,
trellis coded modulation, Turbo Codes.
Information Theory (EESC 6341), Fall 2016
Probability review, Entropy, mutual information, the asymptotic
equipartition property. Lossless compression: Huffman, Shannon, Elias,
and arithmetic coding. Channel capacity: Shannon's channel coding
theorem, discrete channels, Gaussian channels, waveform channels,
elements of rate-distortion theory.
Convex Optimization (EESC 7v85), Fall 2015
Convex sets, functions, and optimization
problems. Basics of convex analysis. Least-squares, linear and
quadratic programs, semidefinite programming, minimax, extremal
volume, and other problems. Optimality conditions, duality theory,
theorems of alternative, and applications. Interior-point
methods. Applications to signal processing, control, communications,
as well as other engineering applications.
Processes (EE 6349), Summer 2004
Probability review, sequences of random variables, convergence, random
processes, continuity, Markov processes, Wiener and Poisson processes,
random signals and linear systems, filtering, prediction and smoothing
Communications (EE 4360), Spring 2004
Baseband signal analysis, PCM, Channel effects: noise and distortion,
Detection of binary signals in noise, Matched filter and correlation
receiver, Intersymbol interference and equalization, ASK, PSK, FSK,
Coherent and non-coherent detection, Error performance, M-ary signaling,
Elements of coding: block codes and their decoding, convolutional codes.
Coding and Compression (EE 7V84), Spring 2001
Lossless and lossy compression of signals. Review of Huffman,
arithmetic and Lempel-Ziv coding. Overview of linear estimation and
prediction, the Levinson-Durbin algorithm. Scalar quantization,
optimality conditions and the Lloyd-Max algorithm. Vector quantization,
optimality and the generalized Lloyd algorithm. Predictive quantization
and performance bounds. Bit allocation and transform
coding. Tree-structured VQ, hierarchical VQ. Advanced topics: trellis
coded quantization (TCQ).
- Digital Signal Processing
Digital signals and systems, digital filter design, the FFT and its
variations, multirate signal processing and wavelets
- Image and Video
Advanced graduate course on image and video compression, image and
- Signals and Systems (undergraduate)
Continuous- and discrete-time linear time-invariant systems; time
domain analysis, Fourier and Laplace frequency domain analysis,
stability, Nyquist sampling.
Last modified Sept. 2006