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Markov Models for Pattern Recognition : From Theory to Applications (Paperback) (Gernot A. Fink)

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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.
Genre: Computers + Internet
Series Title: Advances in Computer Vision and Pattern Recognition
Format: Paperback
Publisher: Springer Verlag
Author: Gernot A. Fink
Language: English
Street Date: September 16, 2016
TCIN: 51706166
UPC: 9781447171331
Item Number (DPCI): 248-30-2196

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