Skip to content

RDLNetworkEcosystem

Sign in Get started

© 2026 Raw Data Library. All rights reserved.

About FAQ Privacy Terms Contact

Generating chaos by an Elman network — Xiang Li (2001) | RDL Network

Home
Publications
Generating chaos by an Elman network

Shared by

City University of Hong Kong

Generating chaos by an Elman network

IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications 48(9): 1126-1131

Article 2001 English

Authors

XL
Xiang Li
ZC
Zengqiang Chen
ZY
Zhuzhi Yuan

Abstract

1 min read

A new nonlinear neuron-activation function is introduced into the framework of an Elman network, thereby enabling the neural network to generate chaos. Basic analysis of its fixed point stability and parameter selection criterion for chaos generation is given, and is verified via simulation studies.

Discussion(0)

Sign in to like and join the discussion.

No comments yet. Be the first to comment.

Publication Info

DOI: 10.1109/81.948441
Year: 2001
Published: —
Language: English

Article Details

Journal Name: IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications
Volume: 48
Issue: 9
Pages: 1126-1131
Link Of The Paper: https://doi.org/10.1109/81.948441

Timeline

Created:June 19, 2026

Related publications

Chaotifying linear Elman networks

Xiang Li, Guanrong Chen, Zengqiang Chen, Zhuzhi Yuan

IEEE Transactions on Neural Networks

GENERATING CHAOS VIA A DYNAMICAL CONTROLLER

Guo‐Qun Zhong, K.F. Man, Guanrong Chen

International Journal of Bifurcation and Chaos

USING DYNAMIC NEURAL NETWORKS TO GENERATE CHAOS: AN INVERSE OPTIMAL CONTROL APPROACH

Edgar N. Sánchez, José P. Pérez, Guanrong Chen

International Journal of Bifurcation and Chaos

A universal circuit for studying and generating chaos. I. Routes to chaos

Leon O Chua, Chai Wah Wu, Anxiang Huang, Guo‐Qun Zhong

Generating chaotic attractors with multiple merged basins of attraction: a switching piecewise-linear control approach

Jinhu Lü, Xinghuo Yu, Guanrong Chen

IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications