Markov Models for Pattern Recognition From Theory to Applications /

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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...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Fink, Gernot A. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008.
Edition:1st ed. 2008.
Subjects:
Pattern recognition systems.
Computer vision.
Natural language processing (Computer science).
Artificial intelligence.
Automated Pattern Recognition.
Computer Vision.
Natural Language Processing (NLP).
Artificial Intelligence.
Online Access:Texto Completo
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.

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