ECE 340 Random Signals

Summer Semester

This course introduces the student to probability and statistics and applies these concepts to the design and analysis of engineering systems, which inherently have noise (random components to their signals). Topics include the axioms of probability, functions of one and two random variables, moments and conditional statistics, correlation and autocorrelation functions, sequences of random variables, and commonly encountered probability distribution/density functions. Applications are primarily focused on Gaussian and Markov processes, matched filters, Wiener filters, mean square estimation, and parameter estimation. Prerequisite: 2.0 or higher in both ECE 332 and EGR 240.

3 credit hours