Bayesian signal processing: classical, modern, and particle filtering methods

✍ Scribed by Candy, James V

• Publisher: IEEE, Wiley
• Year: 2009
• Tongue: English
• Leaves: 637
• Series: Adaptive and learning systems for signal processing communications and control
• Category: Library

✦ Synopsis

New Bayesian approach helps you solve tough problems in signal processing with ease. Signal processing is based on this fundamental conceptthe extraction of critical information from noisy, uncertain data. Most techniques rely on underlying Gaussian assumptions for a solution, but what happens when these assumptions are erroneous? Bayesian techniques circumvent this limitation by offering a completely different approach that can easily incorporate non-Gaussian and nonlinear processes along with all of the usual methods currently available. This text enables readers to fully exploit the many a. Read more...

Abstract:

This book takes the reader from the classical methods of model-based signal processing, to the next generation of processors that will clearly dominate the future of model-based signal processing for years to come. The Bayesian approach is uniformly developed and followed throughout in the algorithms, examples, applications and case studies. Read more...

✦ Table of Contents

Content: Bayestian estimation --
Simulation-based Bayesian methods --
State-space models for Bayesian processing --
Classical Bayesian state-space processors --
Modern Bayesian state-space processors --
Particle-based Bayesian state-space processors --
Joint Bayesian state/parametric processors --
Discrete hidden Markov model Bayesian processors --
Bayesian processors for physics-based applications.

✦ Subjects

Signal processing;Mathematics.;Bayesian statistical decision theory.;COMPUTERS;Information Theory.;TECHNOLOGY & ENGINEERING;Signals & Signal Processing.