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Hidden Semi-Markov models : theory, algorithms and applications /

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 d...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Yu, Shun-Zheng (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam, Netherlands : Elsevier, [2016]
Colección:Computer science reviews and trends.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario: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.
Descripción Física:1 online resource : illustrations.
Bibliografía:Includes bibliographical references.
ISBN:9780128027714
0128027711
0128027673
9780128027677