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Deep learning in time series analysis /

"The concept of deep machine learning becomes easier to understandable by paying attention to the cyclic stochastic time series and a time series whose content is non-stationary not only within the cycles, but also over the cycles as the beat to beat variations. This book introduces original de...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Gharehbaghi, Arash, 1972- (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boca Raton : CRC Press, 2023.
Edición:First edition.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:"The concept of deep machine learning becomes easier to understandable by paying attention to the cyclic stochastic time series and a time series whose content is non-stationary not only within the cycles, but also over the cycles as the beat to beat variations. This book introduces original deep learning methods for classification of such the time series using proposed clustering methods as the learning tools at the deep level"--
Descripción Física:1 online resource.
Bibliografía:Includes bibliographical references and index.
ISBN:9780429321252
0429321252
9781000911435
1000911438
9781000911404
1000911403