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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Detalles Bibliográficos
Otros Autores: Calin Ciufudean (auth), Ciufudean, Calin, editor (editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: [Place of publication not identified] : IntechOpen 2018
2018.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009438408806719
Descripción
Sumario: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.
Descripción Física:1 online resource (124 pages)
Bibliografía:Includes bibliographical references and index.
ISBN:9781838818159
9781789841169
Acceso:Open access