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About this product
- DescriptionThis thoroughly revised and expanded new edition w 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.
- Author BiographyProf. 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.
- Author(s)Gernot A. Fink
- PublisherSpringer London Ltd
- Date of Publication14/10/2016
- SubjectComputing: Professional & Programming
- Series TitleAdvances in Computer Vision and Pattern Recognition
- Place of PublicationEngland
- Country of PublicationUnited Kingdom
- ImprintSpringer London Ltd
- Content Note45 black & white illustrations, biography
- Weight450 g
- Width155 mm
- Height235 mm
- Spine15 mm
- Edition StatementSoftcover reprint of the original 2nd ed. 2014
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