Markov Models for Pattern Recognition: From Theory to Applications

di Gernot A. Fink (Autore)

Springer London Ltd, 2016

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.

• Autore: Gernot A. Fink
• Editore: Springer London Ltd
• Collana: Advances in Computer Vision and Pattern Recognition
• Anno: 2016
• Rilegatura: Paperback / softback
• Pagine: 276 p.
• Dimensioni: 235 x 155 mm
• EAN: 9781447171331

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