Spectral shaping of a white-noise signal. (Image by MIT OpenCourseWare. Courtesy of Prof. Alan Oppenheim and Prof. George Verghese.)
Instructor(s)
Prof. Alan V. Oppenheim
Prof. George Verghese
MIT Course Number
6.011
As Taught In
Spring 2010
Level
Undergraduate
Course Description
Course Features
Course Highlights
This course features a complete set of course notes, Signals, Systems and Inference.
Course Description
This course examines signals, systems and inference as unifying themes 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; 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.
Other Versions
Other OCW Versions
OCW has published multiple versions of this subject. 
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