Particle Filters for Random Set Mod - E-book

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Particle Filters For Random Set Models - ENG

Branko Ristic

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Sinopsis

ISBN:	9781461463160
Formato:	Page Fidelity
Idioma:	Inglés
Editorial:	Springer Nature
Tema:	Matemáticas
Subtema:	Aplicada
Año de publicación:	2013-04-15

This bookÂ 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 basedÂ on the Monte Carlo statistical method. Although the resultingÂ 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.

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