Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications - Computational Memory, Deep Learning, and ... Series in Electronic and Optical Materials) - Image 1

£96.00

Woodhead Publishing Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications - Computational Memory, Deep Learning, and ... Series in Electronic and Optical Materials)

Name: Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications - Computational Memory, Deep Learning, and ... Series in Electronic and Optical Materials)
Brand: Woodhead Publishing
Price: 96.0 GBP
Availability: InStock

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Description

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.

Product Specifications

Brand: Woodhead Publishing
Format: paperback
ASIN: 0081027826
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 26 June 2020
Listed Since: 15 May 2019

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Woodhead Publishing 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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