EE 532 Statistical Signal Analysis
Linear Algebra and linear systems review; Concepts in Estimation Theory: maximum likelihood (ML), maximum a-posteriori (MAP), least squares (LS), minimum mean square (MMSE) estimation; bias, variance, mean squared error, consistency, efficiency; Linear Estimation for Static Systems: LS estimation , polynomial fitting; Linear Dynamic Systems with Random inputs; State Estimation for linear dynamical systems: Kalman Filter; State Estimation in Non-linear Dynamical systems: extended Kalman filter, particle filtering, unscented Kalman filter; Stochastic differential equations
EE 538 Detection and Estimation Theory
Classical statistical decision theory, decision criteria and composite hypothesis tests. Receiver operating characteristics and error probability, applications to radar and communications. Detection of signals with unknown and random parameters, detection of stochastic signals, nonparametric detection techniques. Introduction to signal design, ambiguity function, the uncertanity principle. Applications to radar and sonar systems.
EE 551 Advanced Digital Communications
Elements of a digital communication system, source coding, channel capacity, characterization communication signals and systems, optimum receivers for the additive Gaussian noise channel,signal design for band-limited channels, fading channels, introduction to spread-spectrum communications.
EE 552 Mobile Communication
Carrier and symbol synchronization, block and convolutional channel coding, introduction to multichannel and multi-antenna techniques, equalization.
EE 553 Error Control Coding
Introduction to algebra and Galois fields. Various error control coding techniques including linear block codes, cyclic codes, BCH and Reed-Solomon codes, convolution codes. Viterbi algorithm. Trellis coded modulation.