Download Hidden Markov Models: Estimation and Control by R. J. Elliott, L. Aggoun, J. B. Moore, This work is aimed at mathematics students in the area of stochastic dynamical systems and at engineering graduate students in signal processing and control systems. First-year graduate-level students with some background in systems theory and probability theory can tackle much of this material, at least once the techniques of Chapter 2 are mastered (with reference to the Appendices and some tutorial help). Even so, most of this work is new and would benefit more advanced graduate students.


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

Download the pdf from below to explore all topics of chapters.