A novel chaotic neural network using memristive synapse with applications in associative memory
type: Item
instance of: scholarly article
title: A novel chaotic neural network using memristive synapse with applications in associative memory
zbMATH Open document ID: 1257.68129
DOI: 10.1155/2012/405739
author: Xiaofang Hu
author: Shukai Duan
author: Lidan Wang
published in: Abstract and Applied Analysis
publication date: 2013-02-04T00:00:00Z
review text: Summary: Chaotic Neural Network, also denoted by the acronym CNN, has rich dynamical behaviors that can be harnessed in promising engineering applications. However, due to its complex synapse learning rules and network structure, it is difficult to update its synaptic weights quickly and implement its large scale physical circuit. This paper addresses an implementation scheme of a novel CNN with memristive neural synapses that may provide a feasible solution for further development of CNN. Memristor, widely known as the fourth fundamental circuit element, was theoretically predicted by Chua in 1971 and has been developed in 2008 by the researchers in Hewlett-Packard Laboratory. Memristor based hybrid nanoscale CMOS technology is expected to revolutionize the digital and neuromorphic computation. The proposed memristive CNN has four significant features: (1) nanoscale memristors can simplify the synaptic circuit greatly and enable the synaptic weights update easily; (2) it can separate stored patterns from superimposed input; (3) it can deal with one-to-many associative memory; (4) it can deal with many-to-many associative memory. Simulation results are provided to illustrate the effectiveness of the proposed scheme.
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 94C10
zbMATH DE Number: 6134081
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/405739
OpenAlex ID: W2035721408
Wikidata QID: Q58696538
cites work: Clustering, coding, switching, hierarchical ordering, and control in a network of chaotic elements
cites work: Advances in Neural Networks – ISNN 2005
cites work: Resistance Switching Memories Are Memristors
description: scientific article; zbMATH DE number 6134081