9780387951461 - sequential monte carlo methods in practice (information science and statistics) (18 resultados)
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Librería: Ammareal, Morangis, FranciaAmmareal
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Hardcover. Condición: Bon. Ancien livre de bibliothèque avec équipements. Edition 2001. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Edition 2001. Ammareal gives back up to 15% of this item's net price to charity orga…nizations.
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Tapa Dura. Condición: Bien. Colección 'Statistics for Engineering and Information Science'. Tapa dura. 168 ilustraciones.9780387951461. Springer. Estados Unidos. 2001. 24x16 centímetros. 581 páginas. Tapa dura. Estado=Bien. Inglés.
Sequential Monte Carlo Methods in Practice (Statistics for Engineering and Information Science)
Doucet, Arnaud [Editor]; Freitas, Nando de [Editor]; Gordon, Neil [Editor]; Smith, A. [Foreword];
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hardcover. Condición: New. In shrink wrap. Looks like an interesting title.
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Hardcover. Condición: gut. 2001. Sequential Monte Carlo Methods in Practice In englischer Sprache. pages.
Sequential Monte Carlo Methods in Practice
Doucet, Arnaud (EDT); De Freitas, Nando (EDT); Gordon, Neil (EDT)
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Sequential Monte Carlo Methods in Practice
Doucet, Arnaud (EDT); De Freitas, Nando (EDT); Gordon, Neil (EDT)
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Sequential Monte Carlo Methods in Practice
Doucet, Arnaud (EDT); De Freitas, Nando (EDT); Gordon, Neil (EDT)
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Hardback. Condición: New. 2001 ed. 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 fi…ttest, 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.
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Sequential Monte Carlo Methods in Practice
Doucet, Arnaud (EDT); De Freitas, Nando (EDT); Gordon, Neil (EDT)
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Hardback. Condición: New. 2001 ed. 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 fi…ttest, 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.
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Gebundene Ausgabe. Condición: Neu. Neu neuware, importqualität, auf lager - 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 navigation,robot navigation, econometrics, financial modelling, neuralnetworks,optimal control, optimal filtering, communications,reinforcement learning, signal enhancement, model averaging andselection, computer vision, semiconductor design, population biology,dynamic 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 Paris-XI 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.
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Librería: moluna, Greven, Alemaniamoluna
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Gebunden. Condición: 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.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condición: 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 Mon…te 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.
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This volume presents results in a very active area of research ofinterest to statisticians, engineers, and computer scientists. Theemphasis is on the applications of these important methods.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 616 p…p. Englisch.
