Gernot A. Fink

eBook, PDF

Markov Models for Pattern Recognition (eBook, PDF)

From Theory to Applications

Beschreibung

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.

Technische Details

• Geräte: PC
• ohne Kopierschutz
• Größe: 3.9MB

Barrierefreiheit

• Text-to-Speech

Autor

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.

Produktdetails

• Verlag: Springer London
• Seitenzahl: 276
• Erscheinungstermin: 14. Januar 2014
• Englisch
• ISBN-13: 9781447163084
• Artikelnr.: 43802431

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)