Theory of Segmentation

Hidden Markov Models Theory and Applications Preface......Page 1 Part 1......Page 13 01_History and Theoretical Basics of Hidden Markov Models......Page 15 02_Hidden Markov Models in Dynamic System Modelling and Diagnosis......Page 39 03_Theory of Segmentation......Page 63 04_Classification of Hidden Markov Models: Obtaining Bounds on the Probability of Error and Dealing with Possibly Corrupted Observations......Page 97 Part 2......Page 123 05_Hierarchical Command Recognition Based on Large Margin Hidden Markov Models......Page 125 06_Modeling of Speech Parameter Sequence Considering Global Variance for HMM-Based Speech Synthesis......Page 143 07_Using Hidden Markov Models for ECG Characterisation......Page 163 08_Hidden Markov Models in the Neurosciences......Page 181 09_Volcano-Seismic Signal Detection and Classification Processing Using Hidden Markov Models - Application to San Cristóbal and Telica Volcanoes, Nicaragua......Page 199 10_A Non-Homogeneous Hidden Markov Model for the Analysis of Multi-Pollutant Exceedances Data......Page 219 Part 3......Page 235 11_Continuous Hidden Markov Models for Depth Map-Based Human Activity Recognition......Page 237 12_Applications of Hidden Markov Models in Microarray Gene Expression Data......Page 261 13_Application of HMM to the Study of Three-Dimensional Protein Structure......Page 281 14_Control Theoretic Approach to Platform Optimization using HMM......Page 303 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