Gernot A. Fink

Markov Models for Pattern Recognition

From Theory to Applications

• Gebundenes Buch

Produktbeschreibung

This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n -best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.

Produktdetails

• Advances in Computer Vision and Pattern Recognition
• Verlag: Springer / Springer London / Springer, Berlin
• Artikelnr. des Verlages: 978-1-4471-6307-7
• 2. Aufl.
• Seitenzahl: 292
• Erscheinungstermin: 28. Januar 2014
• Englisch
• Abmessung: 241mm x 160mm x 22mm
• Gewicht: 600g
• ISBN-13: 9781447163077
• ISBN-10: 1447163079
• Artikelnr.: 40034659

Autorenporträt

Prof. Dr.-Ing. Gernot A. Fink is Head of the Pattern Recognition Research Group at TU Dortmund University, Dortmund, Germany. His other publications include the Springer title Markov Models for Handwriting Recognition.

Inhaltsangabe

Introduction.- Application Areas.- Part I: Theory.- Foundations of Mathematical Statistics.- Vector Quantization and Mixture Estimation.- Hidden Markov Models.- N-Gram Models.- Part II: Practice.- Computations with Probabilities.- Configuration of Hidden Markov Models.- Robust Parameter Estimation.- Efficient Model Evaluation.- Model Adaptation.- Integrated Search Methods.- Part III: Systems.- Speech Recognition.- Handwriting Recognition.- Analysis of Biological Sequences.

Rezensionen

From the book reviews:

"The book is highly appropriate for researchers and practitioners dealing with pattern recognition in general and speech, character and handwriting recognition sequences, in particular." (Catalin Stoean, zbMATH 1307.68001, 2015)