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Memristive Devices For Braininspired Computing From Materials Devices And Circuits To Applications Computational Memory Deep Learning And Series In Electronic And Optical Materials 1st Edition Sabina Spiga Editor

  • SKU: BELL-11208870
Memristive Devices For Braininspired Computing From Materials Devices And Circuits To Applications Computational Memory Deep Learning And Series In Electronic And Optical Materials 1st Edition Sabina Spiga Editor
$ 31.00 $ 45.00 (-31%)

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Memristive Devices For Braininspired Computing From Materials Devices And Circuits To Applications Computational Memory Deep Learning And Series In Electronic And Optical Materials 1st Edition Sabina Spiga Editor instant download after payment.

Publisher: Woodhead Publishing
File Extension: PDF
File size: 15.66 MB
Pages: 564
Author: Sabina Spiga (editor), Abu Sebastian (editor), Damien Querlioz (editor), Bipin Rajendran (editor)
ISBN: 9780081027820, 0081027826
Language: English
Year: 2020
Edition: 1

Product desciption

Memristive Devices For Braininspired Computing From Materials Devices And Circuits To Applications Computational Memory Deep Learning And Series In Electronic And Optical Materials 1st Edition Sabina Spiga Editor by Sabina Spiga (editor), Abu Sebastian (editor), Damien Querlioz (editor), Bipin Rajendran (editor) 9780081027820, 0081027826 instant download after payment.

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.

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