| Document Type
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BL
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| Record Number
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666199
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| Doc. No
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dltt
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| Uniform Title
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Mustererkennung mit Markov-Modellen.English
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| Main Entry
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Fink, Gernot A.
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| Title & Author
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Markov models for pattern recognition : : from theory to applications /\ Gernot A. Fink
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| Edition Statement
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Second edition
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Second edition
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| Series Statement
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Advances in computer vision and pattern recognition
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| Page. NO
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1 online resource (xiii, 276 pages) :: illustrations.
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| ISBN
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1447163079 (print)
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: 1447163087 (electronic bk.)
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9781447163077 (print)
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: 9781447163084 (electronic bk.)
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9783540717669
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| Bibliographies/Indexes
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Includes bibliographical references and index
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| Contents
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Introduction -- 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
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| Abstract
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"This comprehensive introduction to the Markov modeling framework describes the underlying theoretical concepts - covering Hidden Markov models and Markov chain models - and presents the techniques and algorithmic solutions essential to creating real world applications. The actual use of Markov models in their three main application areas - namely speech recognition, handwriting recognition, and biological sequence analysis - is presented with examples of successful systems." "Encompassing both Markov model theory and practise, this book addresses the needs of practitioners and researchers from the field of pattern recognition as well as graduate students with a related major field of study."--BOOK JACKET
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| Subject
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Markov processes.
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| Subject
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Pattern perception-- Mathematical models.
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| Dewey Classification
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006.4
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| LC Classification
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Q327.F5613 2014
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| Added Entry
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Ohio Library and Information Network.
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