Random Signals in Communications and Signal Processing

Class Overview

This is a 5000-level version of ECE 4110. This course provides an introduction to models for random signals in discrete and continuous time, Markov chains, Poisson process, queuing processes, power spectral densities, Gaussian random process, response of linear systems to random signals, and elements of estimation and inference as they arise in communications and digital signal processing systems.

Prerequisites: ECE 2720, ECE 3100, and ECE 3250 or equivalents.
Key Topics: Markov Chains, Filtering, Martingales, Diffusion