Memristor and memristive neural networks
This book covers a range of models, circuits and systems built with memristor devices and networks in applications to neural networks. It is divided into three parts: (1) Devices, (2) Models and (3) Applications. The resistive switching property is an important aspect of the memristors, and there ar...
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Year of Publication: | 2018 |
Language: | English |
Physical Description: | 1 online resource (328 pages) |
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(CKB)4970000000099815 (iGPub)INOP0003791 (oapen)https://directory.doabooks.org/handle/20.500.12854/53143 (EXLCZ)994970000000099815 |
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Alex Pappachen James auth Memristor and memristive neural networks IntechOpen 2018 [Place of publication not identified] : IntechOpen, 2018. ©2018 1 online resource (328 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier This book covers a range of models, circuits and systems built with memristor devices and networks in applications to neural networks. It is divided into three parts: (1) Devices, (2) Models and (3) Applications. The resistive switching property is an important aspect of the memristors, and there are several designs of this discussed in this book, such as in metal oxide/organic semiconductor nonvolatile memories, nanoscale switching and degradation of resistive random access memory and graphene oxide-based memristor. The modelling of the memristors is required to ensure that the devices can be put to use and improve emerging application. In this book, various memristor models are discussed, from a mathematical framework to implementations in SPICE and verilog, that will be useful for the practitioners and researchers to get a grounding on the topic. The applications of the memristor models in various neuromorphic networks are discussed covering various neural network models, implementations in A/D converter and hierarchical temporal memories. English COMPUTERS / Data Science / Neural Networks. bisacsh Physical Sciences Engineering and Technology Neural Network Computer and Information Science Numerical Analysis and Scientific Computing 953-51-3947-9 James, Alex Pappachen, editor |
language |
English |
format |
eBook |
author |
Alex Pappachen James |
spellingShingle |
Alex Pappachen James Memristor and memristive neural networks |
author_facet |
Alex Pappachen James James, Alex Pappachen, |
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a p j apj |
author2 |
James, Alex Pappachen, |
author2_variant |
a p j ap apj |
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TeilnehmendeR |
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Alex Pappachen James |
title |
Memristor and memristive neural networks |
title_full |
Memristor and memristive neural networks |
title_fullStr |
Memristor and memristive neural networks |
title_full_unstemmed |
Memristor and memristive neural networks |
title_auth |
Memristor and memristive neural networks |
title_new |
Memristor and memristive neural networks |
title_sort |
memristor and memristive neural networks |
publisher |
IntechOpen IntechOpen, |
publishDate |
2018 |
physical |
1 online resource (328 pages) |
isbn |
953-51-4009-4 953-51-3948-7 953-51-3947-9 |
callnumber-first |
Q - Science |
callnumber-subject |
QA - Mathematics |
callnumber-label |
QA76 |
callnumber-sort |
QA 276 |
illustrated |
Illustrated |
dewey-hundreds |
000 - Computer science, information & general works |
dewey-tens |
000 - Computer science, knowledge & systems |
dewey-ones |
006 - Special computer methods |
dewey-full |
006 |
dewey-sort |
16 |
dewey-raw |
006 |
dewey-search |
006 |
work_keys_str_mv |
AT alexpappachenjames memristorandmemristiveneuralnetworks AT jamesalexpappachen memristorandmemristiveneuralnetworks |
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(CKB)4970000000099815 (iGPub)INOP0003791 (oapen)https://directory.doabooks.org/handle/20.500.12854/53143 (EXLCZ)994970000000099815 |
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Memristor and memristive neural networks |
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1801159555304914944 |
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