Hidden Markov Models, Theory and Applications - Kouemou Guy Leonard; Al-ani Tarik; Lember J<U+00FC>ri; Kuljus Kristi; Koloydenko Alexey et al; InTech
Los modelos ocultos de Markov (hidden Markov models, HMM), aunque conocidos durante dčadas, han tenido un gran avance en la actualidad y an͠ se encuentran en etapa de desarrollo. En este libro se presentan aspectos ter̤icos y una variedad de aplicaciones de estos modelos en sn̕tesis y reconocimiento del habla, medicina, neurociencias, biologa̕ computacional, bioinformt̀ica, sismologa̕, proteccin̤ ambiental e ingeniera̕.El documento se divide en los siguientes capt̕ulos:History and Theoretical Basics of Hidden Markov Models Hidden Markov Models in Dynamic System Modelling and Diagnosis Theory of Segmentation Classification of Hidden Markov Models: Obtaining Bounds on the Probability of Error and Dealing with Possibly Corrupted Observations Hierarchical Command Recognition Based on Large Margin Hidden Markov Models Modeling of Speech Parameter Sequence Considering Global Variance for HMM-Based Speech Synthesis Using Hidden Markov Models for ECG Characterisation Hidden Markov Models in the Neurosciences Volcano-Seismic Signal Detection and Classification Processing Using Hidden Markov Models - Application to San Cristb̤al and Telica Volcanoes, Nicaragua A Non-Homogeneous Hidden Markov Model for the Analysis of Multi-Pollutant Exceedances Data Continuous Hidden Markov Models for Depth Map-Based Human Activity Recognition Applications of Hidden Markov Models in Microarray Gene Expression Data Application of HMM to the Study of Three-Dimensional Protein Structure Control Theoretic Approach to Platform Optimization using HMM