000 02585nam a2200445Ki 4500
001 on1125226233
003 OCoLC
005 20220711203533.0
006 m o d
007 cr cnu---unuuu
008 191029s2019 nju ob 001 0 eng d
040 _aDG1
_beng
_erda
_epn
_cDG1
020 _a9781119507369
_q(electronic bk.)
020 _a1119507367
_q(electronic bk.)
020 _z9781119507383
020 _z1119507383
035 _a(OCoLC)1125226233
050 4 _aQA76.87
_b.Z4757 2019eb
082 0 4 _a006.3/2
_223
049 _aMAIN
100 1 _aZheng, Nan,
_d1989-
_eauthor.
_98590
245 1 0 _aLearning in energy-efficient neuromorphic computing :
_balgorithm and architecture co-design /
_cNan Zheng, Pinaki Mazumder.
264 1 _aHoboken, NJ :
_bWiley-IEEE Press,
_c[2019]
300 _a1 online resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 _aOverview -- Fundamentals and learning of artificial neural networks -- Artificial neural networks in hardware -- Operational principles and learning in SNNs -- Hardware implementations of spiking neural networks.
520 _a"This book focuses on how to build energy-efficient hardware for neural network with learning capabilities. One of the striking features of this book is that it strives to provide a co-design and co-optimization methodologies for building hardware neural networks that can learn. The book provides a complete picture from high-level algorithm to low-level implementation details. The book also covers many fundamentals and essentials in neural networks, e.g., deep learning, as well as hardware implementation of neural networks. This book will serve as a good resource for teaching and training undergraduate and graduate students about the latest generation neural networks with powerful learning capabilities"--
_cProvided by publisher.
588 0 _aPrint version record.
650 0 _aNeural networks (Computer science)
_93414
650 7 _aNeural networks (Computer science)
_2fast
_0(OCoLC)fst01036260
_93414
655 4 _aElectronic books.
_93294
700 1 _aMazumder, Pinaki,
_eauthor.
_98591
776 0 8 _iPrint version:
_aZheng, Nan, 1989-
_tLearning in energy-efficient neuromorphic computing.
_dHoboken, NJ : Wiley-IEEE Press, [2019]
_z9781119507383
_w(DLC) 2019029946
_w(OCoLC)1119074421
856 4 0 _uhttps://doi.org/10.1002/9781119507369
_zWiley Online Library
942 _cEBK
994 _a92
_bDG1
999 _c69145
_d69145