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Sequential Monte Carlo Methods in Practice (Hardcover, 2001 ed.) Loot Price: R7,119
Discovery Miles 71 190
Sequential Monte Carlo Methods in Practice (Hardcover, 2001 ed.): Arnaud Doucet

Sequential Monte Carlo Methods in Practice (Hardcover, 2001 ed.)

Arnaud Doucet; Foreword by A. Smith; Edited by Nando De Freitas, Neil Gordon

Series: Information Science and Statistics

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Loot Price R7,119 Discovery Miles 71 190 | Repayment Terms: R667 pm x 12*

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Monte Carlo methods are revolutionizing the on-line analysis of data in fields as diverse as financial modeling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo filters, particle filters and survival of the fittest, have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modeling, neural networks, optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection, computer vision, semiconductor design, population biology, dynamic Bayesian networks, and time series analysis. This will be of great value to students, researchers and practitioners, who have some basic knowledge of probability. Arnaud Doucet received the Ph. D. degree from the University of Paris-XI Orsay in 1997. From 1998 to 2000, he conducted research at the Signal Processing Group of Cambridge University, UK. He is currently an assistant professor at the Department of Electrical Engineering of Melbourne University, Australia. His research interests include Bayesian statistics, dynamic models and Monte Carlo methods. Nando de Freitas obtained a Ph.D. degree in information engineering from Cambridge University in 1999. He is presently a research associate with the artificial intelligence group of the University of California at Berkeley. His main research interests are in Bayesian statistics and the application of on-line and batch Monte Carlo methods to machine learning. Neil Gordon obtained a Ph.D. in Statistics from Imperial College, University of London in 1993. He is with the Pattern and Information Processing group at the Defence Evaluation and Research Agency in the United Kingdom. His research interests are in time series, statistical data analysis, and pattern recognition with a particular emphasis on target tracking and missile guidance.

General

Imprint: Springer-Verlag New York
Country of origin: United States
Series: Information Science and Statistics
Release date: June 2001
First published: 2001
Editors: Arnaud Doucet
Foreword by: A. Smith
Editors: Nando De Freitas • Neil Gordon
Dimensions: 235 x 155 x 39mm (L x W x T)
Format: Hardcover
Pages: 582
Edition: 2001 ed.
ISBN-13: 978-0-387-95146-1
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
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LSN: 0-387-95146-6
Barcode: 9780387951461

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