6.011 Signals, Systems and Inference


Class Info

Covers signals, systems and inference in communication, control and signal processing. Topics include input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations in discrete and continuous time; and group delay. State feedback and observers. Probabilistic models; stochastic processes, correlation functions, power spectra, spectral factorization. Least-mean square error estimation; Wiener filtering. Hypothesis testing; detection; matched filters.

This class has 6.003, 6.008, 6.041A, and 18.600 as prerequisites.

6.011 will be offered this semester (Spring 2018). It is instructed by A. V. Oppenheim and G. C. Verghese.

Lecture occurs 11:00 AM to 12:00 PM on Mondays and Wednesdays in 32-123.

This class counts for a total of 12 credits.

You can find more information on MIT OpenCourseWare at the Introduction to Communication, Control, and Signal Processing site or on the 6.011 Stellar site.

MIT 6.011 Signals, Systems and Inference Related Textbooks
MIT 6.011 Signals, Systems and Inference On The Web
Introduction to Communication, Control, and Signal Processing
Tags
transform representation state observers state-space models

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