Course description
This is a course in statistical signal processing. In particular, as opposed to a first course is digital signal processing which deals with deterministic signals, this course aims to present methods by which to design signal processing techniques in the presence of uncertainty. This will usually involve an application of some estimation method, which will form the core of the assocated tool or apparatum. The emphasis will be on teaching how varios estimation frameworks yield different signal processing algorithms as opposed to presenting cook-book solutions.
Recommended reading
- B. Porat, Digital Processing of Random Signals: Theory and Methods, Dover Publications (Mineola, NY), 1994
- M. H. Hayes, Statistical Digital Signal Processing and Modeling, Wiley, 1996
Lecture notes
The course material will consist of three principal parts which will cover various aspects of modeling, estimation, and prediction of random signals and events. Specifically, the three parts will cover the follong subjects
Modeling
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Estimation
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Prediction
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