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Hidden Semi-Markov models : theory, algorithms and applications by Yu, Shun-Zheng is a nonfiction available to read on EtoBox.

What is Hidden Semi-Markov models : theory, algorithms and applications about?

Hidden semi-Markov models (HSMMs) are among the most important models in the area of artificial intelligence / machine learning. Since the first HSMM was introduced in 1980 for machine recognition of speech, three other HSMMs have been proposed, with various definitions of duration and observation distributions. Those models have different expressions, algorithms, computational complexities, and applicable areas, without explicitly interchangeable forms. __Hidden Semi-Markov Models: Theory, Algorithms and Applications__ provides a unified and foundational approach to HSMMs, including various HSMMs (such as the explicit duration, variable transition, and residential time of HSMMs), inference and estimation algorithms, implementation methods and application instances. Learn new developments and state-of-the-art emerging topics as they relate to HSMMs, presented with examples drawn from medicine, engineering and computer science. * Discusses the latest developments and emerging topics in the field of HSMMs * Includes a description of applications in various areas including, Human Activity Recognition, Handwriting Recognition, Network Traffic Characterization and Anomaly Detection, and

Who reads Hidden Semi-Markov models : theory, algorithms and applications?

Author

Yu, Shun-Zheng

Publisher

Elsevier Science & Technology Books; Elsevier

Published

2016

Language

EN

ISBN

9780128027714

Category

nonfiction

Subjects

Mathematics, Computer Science, Stem