Input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations. Sampling, discrete-time processing of continuous-time signals. State feedback and observers. Probabilistic models; stochastic processes, correlation functions, power spectra, and whitening filters. Detection; matched filters. Least-mean square error estimation; Wiener filtering.
Instructors: A. V. Oppenheim, G. C. Verghese
Responsibilities taken as Teaching Assistant:
- Develop course material for future MIT Open Course Ware publication.
- Publish solution for weekly problem sets.
- Hold 4 hours of tutorial sessions weekly.