Hidden Markov Models: Estimation and Control / Edition 1

Hidden Markov Models: Estimation and Control / Edition 1

by Robert J Elliott, Lakhdar Aggoun, John B. Moore
     
 

ISBN-10: 0387943641

ISBN-13: 9780387943640

Pub. Date: 12/16/1994

Publisher: Springer New York

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

…  See more details below

Overview

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.

Product Details

ISBN-13:
9780387943640
Publisher:
Springer New York
Publication date:
12/16/1994
Series:
Stochastic Modelling and Applied Probability Series, #29
Edition description:
1st ed. 1995. Corr. 3rd printing 2008
Pages:
362
Product dimensions:
9.21(w) x 6.14(h) x 0.88(d)

Related Subjects

Table of Contents

Preface.- Part I Introduction: 1.Hidden Markov Model Processing.- Part II Discrete-Time HMM Estimation: 2.Discrete States and Discrete Observations.- 3.Continuous-Range Observations.- 4.Continuous-Range States and Observations.- 5.A General Recursive Filter.- 6.Practical Recursive Filters.- Part III Continuous-Time HMM Estimation: 7.Discrete-Range States and Observations.- 8.Markov Chains in Brownian Motion .- Part IV Two-Dimensional HMM Estimation: 9.Hidden Markov Random Fields.- Part V HMM Optimal Control: 10.Discrete-Time HMM Control.- 11.Risk-Sensitive Control of HMM.- 12.Continuous-Time HMM Control.- Appendices: A.Basic Probability Concepts.- B.Continuous-Time Martingale Representation. –References.- Index.

Customer Reviews

Average Review:

Write a Review

and post it to your social network

     

Most Helpful Customer Reviews

See all customer reviews >