Particle Filters for Random Set Models

Branko Ristic

ISBN 10: 1461463157 / ISBN 13: 9781461463153

Published by Springer New York, Springer New York, 2013

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9781461463153

Bibliographic Details

• Title: Particle Filters for Random Set Models
• Publisher: Springer New York, Springer New York
• Publication Date: 2013
• Language: English
• ISBN 10: 1461463157
• ISBN 13: 9781461463153
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 14D millimeters 241 millimeters width by 160 millimeters height by 14 millimeters depth
• Weight: 453 grams

About this title

Synopsis

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, Australia

Defence Science and Technology Organisation, Australia