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portada Markov Models for Pattern Recognition: From Theory to Applications
Type
Physical Book
Author
Publisher
Language
English
Pages
276
Format
Hardcover
Dimensions
23.4x15.6x1.8 cm
Weight
0.59 kg.
ISBN13
9781447163077
Edition No.
0002
Categories

Markov Models for Pattern Recognition: From Theory to Applications

Gernot A. Fink (Author) · Springer · Hardcover

Markov Models for Pattern Recognition: From Theory to Applications - Fink, Gernot A.

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Synopsis "Markov Models for Pattern Recognition: From Theory to Applications"

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.

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