Gernot A. Fink 
Markov Models for Pattern Recognition [PDF ebook] 
From Theory to Applications

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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.

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语言 英语 ● 格式 PDF ● ISBN 9781447163084 ● 出版者 Springer London ● 发布时间 2014 ● 下载 3 时 ● 货币 EUR ● ID 2951612 ● 复制保护 Adobe DRM
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