Advances in Memristor Neural Networks : : Modeling and Applications / / edited by Calin Ciufudean.
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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| Place / Publishing House: | [Place of publication not identified] : : IntechOpen,, 2018. |
| Year of Publication: | 2018 |
| Language: | English |
| Physical Description: | 1 online resource (124 pages) |
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| Summary: | 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. |
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| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 1838818154 178984116X |
| Access: | Open access |
| Hierarchical level: | Monograph |
| Statement of Responsibility: | edited by Calin Ciufudean. |