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Hidden Markov Models

Chapter
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Abstract

Markov chains and hidden Markov models (HMMs) are particular types of PGMs that represent dynamic processes. After a brief introduction to Markov chains, this chapter focuses on hidden Markov models. The algorithms for solving the basic problems: evaluation, optimal sequence, and parameter learning are presented. The chapter concludes with a description of several extensions to the basic HMM, and two applications: the “PageRank” procedure used by Google and gesture recognition.

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Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE)Santa María TonantzintlaMexico

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