Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Stochastic Modelling and Applied Probability (SMAP, volume 29)
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Table of contents (12 chapters)
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Introduction
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Discrete-Time HMM Estimation
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Continuous-Time HMM Estimation
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Two-Dimensional HMM Estimation
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HMM Optimal Control
Keywords
About this book
As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics.
In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors’ general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control.
Authors and Affiliations
Bibliographic Information
Book Title: Hidden Markov Models
Book Subtitle: Estimation and Control
Authors: Robert J. Elliott, John B. Moore, Lakhdar Aggoun
Series Title: Stochastic Modelling and Applied Probability
DOI: https://doi.org/10.1007/978-0-387-84854-9
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag New York 1995
Hardcover ISBN: 978-0-387-94364-0Published: 16 December 1994
Softcover ISBN: 978-1-4419-2841-2Published: 01 December 2010
eBook ISBN: 978-0-387-84854-9Published: 27 September 2008
Series ISSN: 0172-4568
Series E-ISSN: 2197-439X
Edition Number: 1
Number of Pages: XIV, 382
Topics: Systems Theory, Control, Probability Theory and Stochastic Processes, Quantitative Finance