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This book is indexed in
Computer and Information Science » Numerical Analysis and Scientific Computing
Hidden Markov Models, Theory and Applications
Edited by Przemyslaw Dymarski, ISBN 978-953-307-208-1, Hard cover, 314 pages, Publisher: InTech, Chapters published April 19, 2011 under CC BY-NC-SA 3.0 license
DOI: 10.5772/601 
Hidden Markov Models (HMMs), although known for decades, have made a big career nowadays and are still in state of development. This book presents theoretical issues and a variety of HMMs applications in speech recognition and synthesis, medicine, neurosciences, computational biology, bioinformatics, seismology, environment protection and engineering. I hope that the reader will find this book useful and helpful for their own research.
- Chapter 1
History and Theoretical Basics of Hidden Markov Models - Chapter 2 Hidden Markov Models in Dynamic System Modelling and Diagnosis
- Chapter 3 Theory of Segmentation
- Chapter 4 Classification of Hidden Markov Models: Obtaining Bounds on the Probability of Error and Dealing with Possibly Corrupted Observations
- Chapter 5 Hierarchical Command Recognition Based on Large Margin Hidden Markov Models
- Chapter 6 Modeling of Speech Parameter Sequence Considering Global Variance for HMM-Based Speech Synthesis
- Chapter 7 Using Hidden Markov Models for ECG Characterisation
- Chapter 8 Hidden Markov Models in the Neurosciences
- Chapter 9 Volcano-Seismic Signal Detection and Classification Processing Using Hidden Markov Models - Application to San Cristóbal and Telica Volcanoes, Nicaragua
- Chapter 10 A Non-Homogeneous Hidden Markov Model for the Analysis of Multi-Pollutant Exceedances Data
- Chapter 11 Continuous Hidden Markov Models for Depth Map-Based Human Activity Recognition
- Chapter 12 Applications of Hidden Markov Models in Microarray Gene Expression Data
- Chapter 13 Application of HMM to the Study of Three-Dimensional Protein Structure
- Chapter 14 Control Theoretic Approach to Platform Optimization using HMM