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Lessons in Estimation Theory for Signal Processing, Communications, and Control, Second Edition by Jerry M. Mendel - Department of Electrical Engineering, University of Southern California, Los Angeles, California

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Lesson 14 Maximum a Posteriori Estimation of Random Parameters

Summary

MAP estimation is also known as Bayesian estimation. Obtaining a MAP estimate involves specifying both p [Z(k)|θ] and p (θ) and finding the value of θ that maximizes p (θ|Z(k)). Generally, optimization must be used to compute Image. When Z(k) and θ are jointly Gaussian, then we show that Image.

We also examine Image for the generic linear and Gaussian model when H(k) is deterministic, V(k) is ...

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