Overview

This comprehensive introduction to the Markov modeling framework describes the underlying theoretical concepts of Markov models as used for sequential data, covering Hidden Markov models and Markov chain models. It also presents the techniques necessary to build successful systems for practical applications. In addition, the book demonstrates the actual use of the technology in the three main application areas of pattern recognition methods based on Markov-Models: speech recognition, handwriting recognition, and biological sequence analysis. The book is suitable for experts as well as for practitioners.

Full Product Details

Author:   Gernot A. Fink
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   1st ed. Softcover of orig. ed. 2008
Dimensions:   Width: 15.60cm , Height: 1.30cm , Length: 23.40cm
Weight:   0.403kg
ISBN:  

9783642090882

ISBN 10:   3642090885
Pages:   262
Publication Date:   15 October 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Reviews

The practice part makes the book unique among many other pattern recognition textbooks. It discusses implementation details that are often ignored in the literature, but are important in constructing a working system. ! Overall, the book is well written and clear ... It is suited not to those who want to learn the basics of pattern recognition, but to those who want to learn the state of the art of speech, character, and DNA sequence recognition problems from the perspective of the practitioner and designer. ! The depth and breadth of the treatment is right for the intent of the book. (T. Kubota, Lewisburg, PA, in: Computing Reviews, May 2009)

Author Information

Gernot A. Fink earned his diploma in computer science from the University of Erlangen-Nuremberg, Erlangen, Germany, in 1991. He recieved a Ph.D. degree in computer science in 1995 and the venia legendi in applied computer science in 2002 both from Bielefeld University, Germany. Currently, he is professor for Pattern Recognition in Embedded Systems at the University of Dortmund, Germany, where he also heads the Intelligent Systems Group at the Robotics Research Institute. His reserach interests lie in the development and application of pattern recognition methods in the fields of man machine interaction, multimodal machine perception including speech and image processing, statistical pattern recognition, handwriting recognition, and the analysis of genomic data.

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