Open access peer-reviewed Edited Volume

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 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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Advances in Memristor Neural NetworksModeling and ApplicationsEdited by Calin Ciufudean

Published: October 3rd 2018

DOI: 10.5772/intechopen.75147

ISBN: 978-1-78984-116-9

Print ISBN: 978-1-78984-115-2

eBook (PDF) ISBN: 978-1-83881-815-9

Copyright year: 2018

Books open for chapter submissions

5695 Total Chapter Downloads

10 Crossref Citations

3 Web of Science Citations

17 Dimensions Citations


Open access peer-reviewed

1. Synaptic Behavior in Metal Oxide-Based Memristors

By Ping Hu, Shuxiang Wu and Shuwei Li


Open access peer-reviewed

2. The Roadmap to Realize Memristive Three-Dimensional Neuromorphic Computing System

By Hongyu An, Kangjun Bai and Yang Yi


Open access peer-reviewed

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

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


Open access peer-reviewed

4. Memristive Systems Based on Two-Dimensional Materials

By Gennady N. Panin and Olesya O. Kapitanova


Open access peer-reviewed

5. Charge-Controlled Memristor Grid for Edge Detection

By Arturo Sarmiento-Reyes and Yojanes Rodríguez Velásquez


Edited Volume and chapters are indexed in

  • Worldcat
  • OpenAIRE
  • Google Scholar
  • AZ ebsco
  • Base
  • CNKI

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