Markov Models for Pattern Recognition From Theory to Applications /

• Main Author: Fink, Gernot A. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
• Subjects: Computer science.; Artificial intelligence.; Computational linguistics.; Image processing.; Pattern recognition.; Computer Science.; Pattern Recognition.; Image Processing and Computer Vision.; Language Translation and Linguistics.; Artificial Intelligence (incl. Robotics).

Markov models are used to solve challenging pattern recognition problems on the basis of sequential data as, e.g., automatic speech or handwriting recognition. This comprehensive introduction to the Markov modeling framework describes both the underlying theoretical concepts of Markov models - cover...

Table of Contents:

• Application Areas
• Application Areas
• Theory
• Foundations of Mathematical Statistics
• Vector Quantization
• Hidden Markov Models
• n-Gram Models
• Practice
• Computations with Probabilities
• Configuration of Hidden Markov Models
• Robust Parameter Estimation
• Efficient Model Evaluation
• Model Adaptation
• Integrated Search Methods
• Systems
• Speech Recognition
• Character and Handwriting Recognition
• Analysis of Biological Sequences.