Fundamentals of stochastic filtering / by Alan Bain, Dan Crisan.
The objective of stochastic filtering is to determine the best estimate for the state of a stochastic dynamical system from partial observations. The solution of this problem in the linear case is the well known Kalman-Bucy filter which has found widespread practical application. The purpose of this...
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| Main Authors: | , |
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| Format: | Ebook |
| Language: | English |
| Published: |
New York ; London :
Springer,
2009.
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| Series: | Stochastic modelling and applied probability ;
60. |
| Subjects: | |
| Online Access: | Springer eBooks |
| Summary: | The objective of stochastic filtering is to determine the best estimate for the state of a stochastic dynamical system from partial observations. The solution of this problem in the linear case is the well known Kalman-Bucy filter which has found widespread practical application. The purpose of this book is to provide a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. Particular emphasis is placed on the theoretical analysis of numerical methods for the solution of the filtering problem via particle methods. The book should provide sufficient. |
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| Physical Description: | 1 online resource (xiii, 390 pages). |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 0387768963 9780387768960 |