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OverviewThis 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. Full Product DetailsAuthor: Gernot A. FinkPublisher: Springer London Ltd Imprint: Springer London Ltd Edition: 2nd ed. 2014 Dimensions: Width: 15.50cm , Height: 1.70cm , Length: 23.50cm Weight: 0.606kg ISBN: 9781447163077ISBN 10: 1447163079 Pages: 276 Publication Date: 28 January 2014 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsIntroduction.- Application Areas.- Part I: Theory.- Foundations of Mathematical Statistics.- Vector Quantization and Mixture Estimation.- Hidden Markov Models.- N-Gram Models.- Part II: Practice.- Computations with Probabilities.- Configuration of Hidden Markov Models.- Robust Parameter Estimation.- Efficient Model Evaluation.- Model Adaptation.- Integrated Search Methods.- Part III: Systems.- Speech Recognition.- Handwriting Recognition.- Analysis of Biological Sequences.ReviewsFrom 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) 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) Author InformationProf. 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. Tab Content 6Author Website:Countries AvailableAll regions |
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