Articoli correlati a Particle Filters for Random Set Models
Sinossi
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull?autore
Branko Ristic is at the Defence Science and Technology Organisation, Australia
Defence Science and Technology Organisation, AustraliaDalla quarta di copertina
Particle Filters for Random Set Models presents coverage of 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. The resulting algorithms, known as particle filters, in the last decade have become one of the essential tools for stochastic filtering, with applications ranging from navigation and autonomous vehicles to bio-informatics and finance.
While 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. These recent developments have dramatically widened the scope of applications, from single to multiple appearing/disappearing objects, from precise to imprecise measurements and measurement models.
This book is ideal for graduate students, researchers, scientists and engineers interested in Bayesian estimation.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Compra nuovo
Visualizza questo articolo
EUR 127,40
EUR 9,70 per la spedizione da Germania a Italia
Destinazione, tempi e costiAltre edizioni note dello stesso titolo
Risultati della ricerca per Particle Filters for Random Set Models
Foto dell'editore
Particle Filters for Random Set Models
Da: Buchpark, Trebbin, Germania
Valutazione del venditore 5 su 5 stelle
Condizione: Hervorragend. Zustand: Hervorragend | Seiten: 188 | Sprache: Englisch | Produktart: Bücher. Codice articolo 23271958/1
Quantità: 1 disponibili
Immagini fornite dal venditore
Particle Filters for Random Set Models
Print on DemandDa: moluna, Greven, Germania
Valutazione del venditore 5 su 5 stelle
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a hands-on engineering approach to filtering algorithms and their implementation Covers a new generation of particle filters, which are applicable to a much wider class of signal processing applications Includes sensor control for p. Codice articolo 4199034
Quantità: Più di 20 disponibili
Foto dell'editore
Ristic:Particle Filters for Information (eng)
Print on DemandDa: Brook Bookstore On Demand, Napoli, NA, Italia
Valutazione del venditore 5 su 5 stelle
Condizione: new. Questo è un articolo print on demand. Codice articolo 17e2234a7ca992b37a481647b2442f70
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Particle Filters for Random Set Models
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 19659422-n
Quantità: Più di 20 disponibili
Foto dell'editore
Particle Filters for Random Set Models
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. In. Codice articolo ria9781461463153_new
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Particle Filters for Random Set Models
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 19659422-n
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Particle Filters for Random Set Models
Print on DemandDa: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 188 pp. Englisch. Codice articolo 9781461463153
Quantità: 2 disponibili
Immagini fornite dal venditore
Particle Filters for Random Set Models
Editore:
Springer New York, Springer New York Apr 2013, 2013
ISBN 10: 1461463157
ISBN 13: 9781461463153
Nuovo
Rilegato
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: Neu. Neuware -This bookdiscusses 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 188 pp. Englisch. Codice articolo 9781461463153
Quantità: 2 disponibili
Immagini fornite dal venditore
Particle Filters for Random Set Models
Editore:
Springer New York, Springer New York, 2013
ISBN 10: 1461463157
ISBN 13: 9781461463153
Nuovo
Rilegato
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: Neu. 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. Codice articolo 9781461463153
Quantità: 1 disponibili
Immagini fornite dal venditore
Particle Filters for Random Set Models
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: As New. Unread book in perfect condition. Codice articolo 19659422
Quantità: Più di 20 disponibili