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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Markov Models for Pattern Recognition: From Theory to Applications

Markov Models for Pattern Recognition: From Theory to Applications

Fink, Gernot A.

Hardcover

Series: Advances in Computer Vision and Pattern Recognition

General ComputersProgramming

ISBN10: 1447163079
ISBN13: 9781447163077
Publisher: Springer
Published: Jan 28 2014
Pages: 276
Weight: 1.29
Height: 0.69 Width: 6.14 Depth: 9.21
Language: English
This 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.

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