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Full Description
This book presents, in an integrated form, both the analysis and synthesis of three different types of hidden Markov models. Unlike other books on the subject, it is generic and does not focus on a specific theme, e.g. speech processing. Moreover, it presents the translation of hidden Markov models' concepts from the domain of formal mathematics into computer codes using MATLAB®. The unique feature of this book is that the theoretical concepts are first presented using an intuition-based approach followed by the description of the fundamental algorithms behind hidden Markov models using MATLAB®. This approach, by means of analysis followed by synthesis, is suitable for those who want to study the subject using a more empirical approach.
Key Selling Points:
Presents a broad range of concepts related to Hidden Markov Models (HMM), from simple problems to advanced theory
Covers the analysis of both continuous and discrete Markov chains
Discusses the translation of HMM concepts from the realm of formal mathematics into computer code
Offers many examples to supplement mathematical notation when explaining new concepts
Contents
Introduction
1. Probability theory and stochastic processes
2. Discrete hidden Markov models
3. Continuous hidden Markov models
4. Autoregressive Markov models
5. Selected Applications
Glossary
References
Index
