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Kalman Filtering and Neural Networks - Simon Haykin
book is out-of-stock
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Simon Haykin:

Kalman Filtering and Neural Networks - new book

ISBN: 9780471369981

ID: e040f678d0e41a7f9880faf71416bdbe

Die Kalman-Filterung ist ein wichtiges Spezialgebiet der Steuerungstechnik und Signalverarbeitung und die höchstentwickelte Methode für das Design neuronaler Netze. Der unkonventionelle, nichtlineare Ansatz trägt der Tatsache Rechnung, dass in der Praxis meist nichtlineare Probleme von Bedeutung sind. Besprochen werden wichtige Anwendungen, zum Beispiel aus der Steuerungstechnik und der Finanzmathematik. Die Kalman-Filterung ist ein wichtiges Spezialgebiet der Steuerungstechnik und Signalverarbeitung und die höchstentwickelte Methode für das Design neuronaler Netze. Der unkonventionelle, nichtlineare Ansatz trägt der Tatsache Rechnung, dass in der Praxis meist nichtlineare Probleme von Bedeutung sind. Besprochen werden wichtige Anwendungen,zum Beispiel aus der Steuerungstechnik und der Finanzmathematik. State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear. The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter. Other chapters cover: An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF) Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes The dual estimation problem Stochastic nonlinear dynamics: the expectation-maximization (EM) algorithm and the extended Kalman smoothing (EKS) algorithm The unscented Kalman filter Each chapter, with the exception of the introduction, includes illustrative applications of the learning algorithms described here, some of which involve the use of simulated and real-life data. Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems. An Instructor s Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department. Bücher / Fremdsprachige Bücher / Englische Bücher 978-0-471-36998-1, Wiley John + Sons

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Kalman Filtering and Neural Networks - Simon Haykin#Haykin#S. Haykin
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Simon Haykin#Haykin#S. Haykin:

Kalman Filtering and Neural Networks - new book

ISBN: 9780471369981

ID: 6b4f9558caf85c4337ab83530e2320f2

Kalman Filtering and Neural Networks Die Kalman-Filterung ist ein wichtiges Spezialgebiet der Steuerungstechnik und Signalverarbeitung und die höchstentwickelte Methode für das Design neuronaler Netze. Der unkonventionelle, nichtlineare Ansatz trägt der Tatsache Rechnung, dass in der Praxis meist nichtlineare Probleme von Bedeutung sind. Besprochen werden wichtige Anwendungen,zum Beispiel aus der Steuerungstechnik und der Finanzmathematik. State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear. The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter. Other chapters cover: An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF) Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes The dual estimation problem Stochastic nonlinear dynamics: the expectation-maximization (EM) algorithm and the extended Kalman smoothing (EKS) algorithm The unscented Kalman filter Each chapter, with the exception of the introduction, includes illustrative applications of the learning algorithms described here, some of which involve the use of simulated and real-life data. Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems. An Instructor s Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department. Bücher / Fremdsprachige Bücher / Englische Bücher 978-0-471-36998-1, John Wiley & Sons

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Kalman Filtering and Neural Networks - Simon Haykin
book is out-of-stock
(*)
Simon Haykin:
Kalman Filtering and Neural Networks - new book

ISBN: 9780471369981

ID: e040f678d0e41a7f9880faf71416bdbe

Kalman Filtering and Neural Networks Die Kalman-Filterung ist ein wichtiges Spezialgebiet der Steuerungstechnik und Signalverarbeitung und die höchstentwickelte Methode für das Design neuronaler Netze. Der unkonventionelle, nichtlineare Ansatz trägt der Tatsache Rechnung, dass in der Praxis meist nichtlineare Probleme von Bedeutung sind. Besprochen werden wichtige Anwendungen,zum Beispiel aus der Steuerungstechnik und der Finanzmathematik. State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear. The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter. Other chapters cover: An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF) Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes The dual estimation problem Stochastic nonlinear dynamics: the expectation-maximization (EM) algorithm and the extended Kalman smoothing (EKS) algorithm The unscented Kalman filter Each chapter, with the exception of the introduction, includes illustrative applications of the learning algorithms described here, some of which involve the use of simulated and real-life data. Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems. An Instructor s Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department. Bücher / Fremdsprachige Bücher / Englische Bücher 978-0-471-36998-1, John Wiley & Sons Inc

New book Buch.de
Nr. 1094301 Shipping costs:Bücher und alle Bestellungen die ein Buch enthalten sind versandkostenfrei, sonstige Bestellungen innerhalb Deutschland EUR 3,-, ab EUR 20,- kostenlos, Bürobedarf EUR 4,50, kostenlos ab EUR 45,-, Versandfertig in 1 - 2 Wochen, DE. (EUR 0.00)
Details...
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Kalman Filtering and Neural Networks - Simon Haykin
book is out-of-stock
(*)
Simon Haykin:
Kalman Filtering and Neural Networks - new book

ISBN: 9780471369981

ID: e040f678d0e41a7f9880faf71416bdbe

Kalman Filtering and Neural Networks Die Kalman-Filterung ist ein wichtiges Spezialgebiet der Steuerungstechnik und Signalverarbeitung und die höchstentwickelte Methode für das Design neuronaler Netze. Der unkonventionelle, nichtlineare Ansatz trägt der Tatsache Rechnung, dass in der Praxis meist nichtlineare Probleme von Bedeutung sind. Besprochen werden wichtige Anwendungen,zum Beispiel aus der Steuerungstechnik und der Finanzmathematik. State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear. The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter. Other chapters cover: An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF) Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes The dual estimation problem Stochastic nonlinear dynamics: the expectation-maximization (EM) algorithm and the extended Kalman smoothing (EKS) algorithm The unscented Kalman filter Each chapter, with the exception of the introduction, includes illustrative applications of the learning algorithms described here, some of which involve the use of simulated and real-life data. Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems. An Instructor s Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department. Bücher / Fremdsprachige Bücher / Englische Bücher 978-0-471-36998-1, Wiley John + Sons

New book Buch.de
Nr. 1094301 Shipping costs:Bücher und alle Bestellungen die ein Buch enthalten sind versandkostenfrei, sonstige Bestellungen innerhalb Deutschland EUR 3,-, ab EUR 20,- kostenlos, Bürobedarf EUR 4,50, kostenlos ab EUR 45,-, Versandfertig in 1 - 2 Wochen, DE. (EUR 0.00)
Details...
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Kalman Filtering and Neural Networks - Haykin, Simon
book is out-of-stock
(*)
Haykin, Simon:
Kalman Filtering and Neural Networks - new book

ISBN: 9780471369981

ID: 152678

State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear. The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter. Other chapters cover: An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF) Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes The dual estimation problem Stochastic nonlinear dynamics: the expectation-maximization (EM) algorithm and the extended Kalman smoothing (EKS) algorithm The unscented Kalman filter Each chapter, with the exception of the introduction, includes illustrative applications of the learning algorithms described here, some of which involve the use of simulated and real-life data. Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems. An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department. Technology Technology eBook, Wiley

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Details of the book
Kalman Filtering and Neural Networks
Author:

Haykin, Simon; Haykin

Title:

Kalman Filtering and Neural Networks

ISBN:

9780471369981

Die Kalman-Filterung ist ein wichtiges Spezialgebiet der Steuerungstechnik und Signalverarbeitung und die höchstentwickelte Methode für das Design neuronaler Netze. Der unkonventionelle, nichtlineare Ansatz trägt der Tatsache Rechnung, dass in der Praxis meist nichtlineare Probleme von Bedeutung sind. Besprochen werden wichtige Anwendungen, zum Beispiel aus der Steuerungstechnik und der Finanzmathematik.

Details of the book - Kalman Filtering and Neural Networks


EAN (ISBN-13): 9780471369981
ISBN (ISBN-10): 0471369985
Hardcover
Publishing year: 2001
Publisher: John Wiley & Sons
304 Pages
Weight: 0,544 kg
Language: eng/Englisch

Book in our database since 29.05.2007 04:06:57
Book found last time on 27.10.2016 17:40:19
ISBN/EAN: 9780471369981

ISBN - alternate spelling:
0-471-36998-5, 978-0-471-36998-1

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