Advances in Memristor Neural Networks - Modeling and Applications
Nowadays, scientific research deals with alternative solutions for creating non-traditional computing systems, such as neural network architectures where the stochastic nature and live dynamics of memristive models play a key role. The features of memristors make it possible to direct processing and...
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| Format: | Book Chapter |
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IntechOpen
2018
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| Online Access: | Get Fullteks DOAB: description of the publication |
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| LEADER | 01938naaaa2200301uu 4500 | ||
|---|---|---|---|
| 001 | doab_20_500_12854_40308 | ||
| 005 | 20210211 | ||
| 020 | |a intechopen.75147 | ||
| 020 | |a 9781789841152 | ||
| 020 | |a 9781789841169 | ||
| 024 | 7 | |a 10.5772/intechopen.75147 |c doi | |
| 041 | 0 | |a English | |
| 042 | |a dc | ||
| 100 | 1 | |a Calin Ciufudean |4 auth | |
| 245 | 1 | 0 | |a Advances in Memristor Neural Networks - Modeling and Applications |
| 260 | |b IntechOpen |c 2018 | ||
| 300 | |a 1 electronic resource (124 p.) | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a Nowadays, scientific research deals with alternative solutions for creating non-traditional computing systems, such as neural network architectures where the stochastic nature and live dynamics of memristive models play a key role. The features of memristors make it possible to direct processing and analysis of both biosystems and systems driven by artificial intelligence, as well as develop plausible physical models of spiking neural networks with self-organization. This book deals with advanced applications illustrating these concepts, and delivers an important contribution for the achievement of the next generation of intelligent hybrid biostructures. Different modeling and simulation tools can deliver an alternative to funding the theoretical approach as well as practical implementation of memristive systems. | ||
| 540 | |a All rights reserved |4 http://oapen.org/content/about-rights | ||
| 546 | |a English | ||
| 653 | |a Engineering | ||
| 653 | |a Physical Sciences | ||
| 653 | |a Engineering and Technology | ||
| 653 | |a Electrical and Electronic Engineering | ||
| 653 | |a Mathematical Modeling | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://www.intechopen.com/books/advances-in-memristor-neural-networks-modeling-and-applications |7 0 |z Get Fullteks |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/40308 |7 0 |z DOAB: description of the publication |