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
Otros Autores: Gharehbaghi, Arash, 1972- author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Boca Raton, FL : CRC Press 2023.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009757916606719
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 (208 pages)
Bibliografía:Includes bibliographical references and index.
ISBN:9780429321252
9781000911435