Articles liés à Sequential Monte Carlo Methods in Practice
Synopsis
This volume presents results in a very active area of research of interest to statisticians, engineers, and computer scientists. The emphasis is on the applications of these important methods.
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Présentation de l'éditeur
Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They 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.
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Sequential Monte Carlo Methods in Practice (Information Science and Statistics)
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Sequential Monte Carlo Methods in Practice
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Springer New York, 2010
ISBN 10 : 1441928871
ISBN 13 : 9781441928870
Neuf
Couverture souple
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. - Monte Carlo Methods is a very hot area of research- Book s emphasis is on applications that span many disciplines- requires only basic knowledge of probabilityMonte Carlo methods are revolutionizing the on-line analysis of data in many fileds. N° de réf. du vendeur 4173359
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Sequential Monte Carlo Methods in Practice
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Springer New York, Chapman And Hall/CRC Dez 2010, 2010
ISBN 10 : 1441928871
ISBN 13 : 9781441928870
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Monte Carlo methods are revolutionising the on-line analysis of data in fields as diverse as financial modelling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo filters, particle filters and survial of the fittest, have made it possible to solve numerically many complex, non-standarard 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 modelling, 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 practicioners, 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. 616 pp. Englisch. N° de réf. du vendeur 9781441928870
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Sequential Monte Carlo Methods in Practice (Information Science and Statistics)
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Springer, 2010
ISBN 10 : 1441928871
ISBN 13 : 9781441928870
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paperback. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_345552435
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Sequential Monte Carlo Methods in Practice
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Springer New York, Springer US, 2010
ISBN 10 : 1441928871
ISBN 13 : 9781441928870
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Monte Carlo methods are revolutionising the on-line analysis of data in fields as diverse as financial modelling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo filters, particle filters and survial of the fittest, have made it possible to solve numerically many complex, non-standarard 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 modelling, 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 practicioners, 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. N° de réf. du vendeur 9781441928870
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Sequential Monte Carlo Methods in Practice
Edité par
Springer New York, Springer US Dez 2010, 2010
ISBN 10 : 1441928871
ISBN 13 : 9781441928870
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. Neuware -Monte Carlo methods are revolutionising the on-line analysis of datain fields as diverse as financial modelling, target tracking andcomputer vision. These methods, appearing under the names of bootstrapfilters, condensation, optimal Monte Carlo filters, particle filtersand survial of the fittest, have made it possible to solve numericallymany complex, non-standarard problems that were previouslyintractable.This book presents the first comprehensive treatment of thesetechniques, including convergence results and applications totracking, guidance, automated target recognition, aircraft navigationrobot navigation, econometrics, financial modelling, neuralnetworks,optimal control, optimal filtering, communicationsreinforcement learning, signal enhancement, model averaging andselection, computer vision, semiconductor design, population biologydynamic Bayesian networks, and time series analysis. This will be ofgreat value to students, researchers and practicioners, who have somebasic knowledge of probability.Arnaud Doucet received the Ph. D. degree from the University of ParisXI Orsay in 1997. From 1998 to 2000, he conducted research at theSignal Processing Group of Cambridge University, UK. He is currentlyan assistant professor at the Department of Electrical Engineering ofMelbourne University, Australia. His research interests includeBayesian statistics, dynamic models and Monte Carlo methods.Nando de Freitas obtained a Ph.D. degree in information engineeringfrom Cambridge University in 1999. He is presently a researchassociate with the artificial intelligence group of the University ofCalifornia at Berkeley. His main research interests are in Bayesianstatistics and the application of on-line and batch Monte Carlomethods to machine learning.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 616 pp. Englisch. N° de réf. du vendeur 9781441928870
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Sequential Monte Carlo Methods in Practice (Information Science and Statistics)
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