Signals and Systems

Catalog description

The main goal of this course is to develop the theory of classical signals and systems analysis for both continuous- and discrete-time cases. Topics include signal and system properties, linear time-invariant systems, stability analysis, sampling of continuous-time signals, the z-transform, the discrete Fourier transform, time- and frequency-domain representations of discrete-time signals and systems, and introductory concepts in stochastic signals and systems. The course also introduces statistical inference applications through the use of the Kalman filter for maximum likelihood parameter estimation and state estimation.