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By
Dan Crisan (editor) and
Boris Rozovskii (editor)
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Jump down to see edition details for: Hardcover
Bibliographic Detail
Publisher
Oxford Univ Pr
Publication date
April 15, 2011
Pages
1063
Binding
Hardcover
Book category
Adult Non-Fiction
ISBN-13
9780199532902
ISBN-10
0199532907
Dimensions
2.50 by 7 by 10 in.
Weight
4.34 lbs.
Published in
Great Britain
Original list price
$210.00
Other format details
university press
Amazon.com says people who bought this book also bought:
Markov Chains and Stochastic Stability | Statistics of Random Processes I | Data Science at the Command Line
Markov Chains and Stochastic Stability | Statistics of Random Processes I | Data Science at the Command Line
Summaries and Reviews
Amazon.com description: Product Description: In many areas of human endeavor, the systems involved are not available for direct measurement. Instead, by combining mathematical models for a system's evolution with partial observations of its evolving state, we can make reasonable inferences about it. The increasing complexity of the modern world makes this analysis and synthesis of high-volume data an essential feature in many real-world problems.
The celebrated Kalman-Bucy filter, designed for linear dynamical systems with linearly structured measurements, is the most famous Bayesian filter. Its generalizations to nonlinear systems and/or observations are collectively referred to as nonlinear filtering (NLF), an extension of the Bayesian framework to the estimation, prediction, and interpolation of nonlinear stochastic dynamics. NLF uses a stochastic model to make inferences about an evolving system and is a theoretically optimal algorithm.
The breadth of its applications, firmly established and still emerging, is simply astounding. Early uses such as cryptography, tracking, and guidance were mostly of a military nature. Since then, the scope has exploded. It includes the study of global climate, estimating the state of the economy, identifying tumors using non-invasive methods, and much more.
The Oxford Handbook of Nonlinear Filtering is the first comprehensive written resource for the subject. It contains classical and recent results and applications, with contributions from 58 authors. Collated into 10 parts, it covers the foundations of nonlinear filtering, connections to stochastic partial differential equations, stability and asymptotic analysis, estimation and control, approximation theory and numerical methods for solving the nonlinear filtering problem (including particle methods). It also contains a part dedicated to the application of nonlinear filtering to several problems in mathematical finance.
The celebrated Kalman-Bucy filter, designed for linear dynamical systems with linearly structured measurements, is the most famous Bayesian filter. Its generalizations to nonlinear systems and/or observations are collectively referred to as nonlinear filtering (NLF), an extension of the Bayesian framework to the estimation, prediction, and interpolation of nonlinear stochastic dynamics. NLF uses a stochastic model to make inferences about an evolving system and is a theoretically optimal algorithm.
The breadth of its applications, firmly established and still emerging, is simply astounding. Early uses such as cryptography, tracking, and guidance were mostly of a military nature. Since then, the scope has exploded. It includes the study of global climate, estimating the state of the economy, identifying tumors using non-invasive methods, and much more.
The Oxford Handbook of Nonlinear Filtering is the first comprehensive written resource for the subject. It contains classical and recent results and applications, with contributions from 58 authors. Collated into 10 parts, it covers the foundations of nonlinear filtering, connections to stochastic partial differential equations, stability and asymptotic analysis, estimation and control, approximation theory and numerical methods for solving the nonlinear filtering problem (including particle methods). It also contains a part dedicated to the application of nonlinear filtering to several problems in mathematical finance.
Editions
Hardcover
The price comparison is for this edition
With Dan Crisan (other contributor) |
from Oxford Univ Pr (April 15, 2011)
9780199532902 | details & prices | 1063 pages | 7.00 × 10.00 × 2.50 in. | 4.34 lbs | List price $210.00
About: In many areas of human endeavor, the systems involved are not available for direct measurement.
About: In many areas of human endeavor, the systems involved are not available for direct measurement.
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