TEL 515E - Statist.Signal Processing

Course Objectives

Analysis of linear systems with stationary random inputs
Parametric modeling of random signals
Optimum digital filter design
Power spectrum estimation of random processes

Course Description

Fundamentals of discrete time signal processing. Discrete random processes. Random variables, vectors and sequences. Analysis of linear systems with stationary random inputs. Innovation representation of random vectors. Signal modelling, AR, MA, ARMA models. Levinson and Schür algorithms. Optimum linear filters. Solution of normal equations. Linear prediction. Algorithms and structures for optimum linear filters. Wiener and Kalman filters. Signal modeling and parametric spectral estimation