— Estimation & Detection of Signals in Noise

Prerequisites & course information

Course Description: Introduction to parameter estimation and detections of signals in noise. Bayes and Neyman-Pearson likelihood-ratio tests for signal detection. Maximum-likelihood parameter estimation. Detection of known and Gaussian signals in white or colored noise. Applications to communications, radar, signal processing. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Grade Mode: Letter. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Grade Mode: Letter.