Sparsity in Bayesian Signal Estimation

Abstract

The Bayesian view of probability leads to statistical inferences expressed as probability distributions for uncertain parameters, computed by updating initial beliefs or uncertainty according to new data, using Bayes' theorem. These inferences can be computed analytically in some simple settings, but computationally demanding numerical integrations are often required. © 2011 Elsevier Inc.