Advances in Memristor Neural Networks - Modeling and Applications

Edited by Calin Ciufudean

in Books from IntechOpen

Abstract: 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.

JEL-codes: C60 (search for similar items in EconPapers)
Date: 2018
ISBN: 978-1-78984-115-2
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Book downloadable chapter-by-chapter

Chapters in this book:

Charge-Controlled Memristor Grid for Edge Detection

Arturo Sarmiento Reyes and Yojanes R. Velasquez

Memristive Anodic Oxides: Production, Properties and Applications in Neuromorphic Computing

Andrea Brenna, Fernando Corinto, Seyedreza Noori, Marco Ormellese, MariaPia Pedeferri and Maria Vittoria Diamanti

Memristive Systems Based on Two-Dimensional Materials

Gennady Panin and Olesya O. Kapitanova

Synaptic Behavior in Metal Oxide-Based Memristors

Ping Hu, Shuxiang Wu and Shuwei Li

The Roadmap to Realize Memristive Three-Dimensional Neuromorphic Computing System

Hongyu An, Kangjun Bai and Yang Cindy Yi

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Persistent link: https://EconPapers.repec.org/RePEc:ito:pbooks:5270

DOI: 10.5772/intechopen.75147

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