Associative chaotic neural network via exponential decay spatio-temporal effect

Authors:
Shukai Duan;Lidan Wang
Affiliations:
School of Electronic Information Engineering, Southwest China Normal University, Chongqing, China;School of Electronic Information Engineering, Southwest China Normal University, Chongqing, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Year:
2005

Citing 2
Cited 0

Clustering, coding, switching, hierarchical ordering, and control in a network of chaotic elements

Physica D
A network of chaotic elements for information processing

Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a novel associative chaotic neural network (NACNN) via exponential decay effect. We replace historic spatio-temporal effect on neural network with new exponential decay parameters, which is more close to the facts. As we know, historic effect on our memory always decreases at exponential level with the time increasing. The proposed model can realize one-to-many associations perfectly. The effectiveness of our scheme is illustrated by a series of computer simulations.