Particle Filters for Random Set Models (Paperback)

Particle Filters for Random Set Models By Branko Ristic Cover Image
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This book discusses state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based on the Monte Carlo statistical method. Although the resulting algorithms, known as particle filters, have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. This book is ideal for graduate students, researchers, scientists and engineers interested in Bayesian estimation.

About the Author

Branko Ristic is at the Defence Science and Technology Organisation, AustraliaDefence Science and Technology Organisation, Australia

Product Details
ISBN: 9781489988843
ISBN-10: 148998884X
Publisher: Springer
Publication Date: May 22nd, 2015
Pages: 174
Language: English