Hidden Markov models : estimation and control
Author(s)
Bibliographic Information
Hidden Markov models : estimation and control
（Stochastic modelling and applied probability, 29）
Springer, 2008, c1995
[2nd ed]
Related Bibliography 1 items
Available at / 2 libraries
-
No Libraries matched.
- Remove all filters.
Note
"Corrected, 3rd printing 2008" -- T.p. verso
Includes bibliographical references (p. 365-[372]) and indexes
Description and Table of Contents
Description
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.
Table of Contents
Hidden Markov Model Processing.- Discrete-Time HMM Estimation.- Discrete States and Discrete Observations.- Continuous-Range Observations.- Continuous-Range States and Observations.- A General Recursive Filter.- Practical Recursive Filters.- Continuous-Time HMM Estimation.- Discrete-Range States and Observations.- Markov Chains in Brownian Motion.- Two-Dimensional HMM Estimation.- Hidden Markov Random Fields.- HMM Optimal Control.- Discrete-Time HMM Control.- Risk-Sensitive Control of HMM.- Continuous-Time HMM Control.
by "Nielsen BookData"