Probabilistic Inference in Signal Processing
In this chapter, the fundamental concepts and techniques underlying Bayesian inference are reviewed. We begin with a definition of the key problem of data analysis, which is to interpret data in the presence of noise. We advocate a Bayesian approach to this problem.
KeywordsGeneral Linear Model Likelihood Function Prior Probability Posterior Density Nuisance Parameter
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