Markov Models for Pattern Recognition: From Theory to Applications - Softcover

Fink, Gernot A.

Softcover

ISBN 10: 3540717668 ISBN 13: 9783540717669

Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 2007

Synopsis

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.

About this title

About the Author

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.

From the Back Cover

Markov models are used to solve challenging pattern recognition problems
on the basis of sequential data as, e.g., automatic speech or handwriting
recognition. This comprehensive introduction to the Markov modeling framework
describes both the underlying theoretical concepts of Markov models - covering
Hidden Markov models and Markov chain models - as used for sequential data and
presents the techniques necessary to build successful systems for practical
applications.

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.

Edition details

• Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
• Publication date: 2007
• Language: English
• ISBN 10: 3540717668
• ISBN 13: 9783540717669
• Binding: Paperback
• Number of pages: 260