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Memristive devices for brain-inspired computing [electronic resource] : from materials, devices, and circuits to applications : computational memory, deep learning, and spiking neural networks / edited by Sabina Spiga ... [et al.].
- 其他作者:
- 出版: Duxford ;Cambridge, MA : Woodhead Publishing 2020.
- 叢書名: Woodhead Publishing series in electronic and optical materials
- 主題: Neural networks (Computer science) , Memristors. , Memristors , Neural networks (Computer science) , Electronic books.
- ISBN: 0081027826 (electronic bk.) 、 9780081027820 (electronic bk.) 、 9780081027875 (electronic bk.) 、 0081027877 (electronic bk.) 、 9780081027820 (print)
- URL:
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- 一般註:Includes bibliographical references and index. 110年度臺灣學術電子書暨資料庫聯盟採購
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讀者標籤:
- 系統號: 000291907 | 機讀編目格式
館藏資訊

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.
摘要註
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.




