Publisher's Synopsis
Written as a self-learning guide, this book deals with the treatment of the Variational Bayes (VB) approximation in signal processing. It reviews the VB distributional approximation, showing that tractable algorithms for parametric model identification can be generated in off-line and on-line contexts.