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Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications - Computational Memory, Deep Learning, and ... Series in Electronic and Optical Materials) - Softcover
- PublisherWoodhead Publishing
- Publication date2020
- ISBN 10 0081027826
- ISBN 13 9780081027820
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages564
- EditorSpiga Sabina, Sebastian Abu, Querlioz Damien, Rajendran Bipin
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Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications - Computational Memory, Deep Learning, and . Series in Electronic and Optical Materials)
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Memristive Devices for Brain-Inspired Computing
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Elsevier Science & Technology, Woodhead Publishing, 2020
ISBN 10: 0081027826
ISBN 13: 9780081027820
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications-Computational Memory, Deep Learning, and Spiking Neural Networks reviews the latest in material and devices engineering for optimizing memristive devices beyond storage applications and toward brain-inspired computing. The book provides readers with an understanding of four key concepts, including materials and device aspects with a view of current materials systems and their remaining barriers, algorithmic aspects comprising basic concepts of neuroscience as well as various computing concepts, the circuits and architectures implementing those algorithms based on memristive technologies, and target applications, including brain-inspired computing, computational memory, and deep learning. This comprehensive book is suitable for an interdisciplinary audience, including materials scientists, physicists, electrical engineers, and computer scientists. Englisch. Seller Inventory # 9780081027820
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Memristive Devices for Brain-Inspired Computing: From Materials, Devices and Circuits to Applications - Computational Memory, Deep Learning, and Spiki
Published by
Elsevier Science & Technology|Woodhead Publishing, 2020
ISBN 10: 0081027826
ISBN 13: 9780081027820
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications-Computational Memory, Deep Learning, and Spiking Neural Networks reviews the latest in material and devices engineering for optimizing memristiv. Seller Inventory # 294028091
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Memristive Devices for Brain-inspired Computing : From Materials, Devices, and Circuits to Applications - Computational Memory, Deep Learning, and Spiking Neural Networks
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Memristive Devices for Brain-Inspired Computing : From Materials, Devices, and Circuits to Applications - Computational Memory, Deep Learning, and Spiking Neural Networks
Published by
Elsevier Science & Technology, Woodhead Publishing, 2020
ISBN 10: 0081027826
ISBN 13: 9780081027820
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Taschenbuch
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications-Computational Memory, Deep Learning, and Spiking Neural Networks reviews the latest in material and devices engineering for optimizing memristive devices beyond storage applications and toward brain-inspired computing. The book provides readers with an understanding of four key concepts, including materials and device aspects with a view of current materials systems and their remaining barriers, algorithmic aspects comprising basic concepts of neuroscience as well as various computing concepts, the circuits and architectures implementing those algorithms based on memristive technologies, and target applications, including brain-inspired computing, computational memory, and deep learning. This comprehensive book is suitable for an interdisciplinary audience, including materials scientists, physicists, electrical engineers, and computer scientists. Seller Inventory # 9780081027820
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