Hardware architectures for deep learning /

This book discusses innovative ideas in the design, modelling, implementation, and optimization of hardware platforms for neural networks. The book provides an overview of this emerging field, from principles to applications, for researchers, postgraduate students and engineers who work on learning-...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Daneshtalab, Masoud, 1979- (Editor ), Modarressi, Mehdi (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Stevenage, United Kingdom : The Institution of Engineering and Technology, 2020.
Colección:Materials, circuits and devices series ; 55.
Temas:
Computer architecture.
Machine learning.
Neural networks (Computer science)
Neural Networks, Computer
Machine Learning
Ordinateurs > Architecture.
Apprentissage automatique.
Réseaux neuronaux (Informatique)
Computer architecture
Machine learning
feedforward neural nets.
learning (artificial intelligence)
neural chips.
neural net architecture.
neuromorphic engineering.
recurrent neural nets.
Acceso en línea:Texto completo
Descripción
Sumario:This book discusses innovative ideas in the design, modelling, implementation, and optimization of hardware platforms for neural networks. The book provides an overview of this emerging field, from principles to applications, for researchers, postgraduate students and engineers who work on learning-based services and hardware platforms.
Descripción Física:1 online resource (xix, 306 pages) : illustrations (some color)
Bibliografía:Includes bibliographical references and index (pages 297-306).
ISBN:9781785617690
1785617699
1523129697
9781523129690

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