000			03075cam a2200493 i 4500
001			on1159208501
003			OCoLC
005			20230516165857.0
006			m o d
007			cr cnu---unuuu
008			200622s2020 enka ob 001 0 eng d
040			_aYDX _beng _erda _epn _cYDX _dYDXIT _dOPELS _dN$T _dOPELS _dUKAHL _dUKMGB _dOCLCF _dOCLCQ _dOCLCO _dK6U _dOCLCQ
015			_aGBC055133 _2bnb
016	7		_a019786215 _2Uk
020			_a0081027826 _q(electronic bk.)
020			_a9780081027820 _q(electronic bk.)
020			_a9780081027875 _q(electronic bk.)
020			_a0081027877 _q(electronic bk.)
020			_z9780081027820 _q(print)
035			_a(OCoLC)1159208501
050		4	_aQA76.87 _b.M46 2020
082	0	4	_a006.3/2 _223
245	0	0	_aMemristive devices for brain-inspired computing : _bfrom materials, devices, and circuits to applications : computational memory, deep learning, and spiking neural networks / _cedited by Sabina Spiga [and three others].
264		1	_aDuxford ; _aCambridge, MA : _bWoodhead Publishing, _c[2020]
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	0		_aWoodhead Publishing series in electronic and optical materials
504			_aIncludes bibliographical references and index.
588	0		_aOnline resource; title from digital title page (viewed on June 30, 2020).
520			_aMemristive 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.
650		0	_aNeural networks (Computer science) _93414
650		0	_aMemristors. _968799
650		2	_aNeural Networks, Computer _0(DNLM)D016571 _921566
650		6	_aR�eseaux neuronaux (Informatique) _0(CaQQLa)201-0209597 _965728
650		6	_aMemristances. _0(CaQQLa)000281637 _968800
650		7	_aMemristors _2fast _0(OCoLC)fst01894553 _968799
650		7	_aNeural networks (Computer science) _2fast _0(OCoLC)fst01036260 _93414
700	1		_aSpiga, Sabina, _eeditor. _968801
776	0	8	_iPrint version: _z0081027826 _z9780081027820 _w(OCoLC)1102156713
856	4	0	_3ScienceDirect _uhttps://www.sciencedirect.com/science/book/9780081027820
942			_cEBK
999			_c82457 _d82457