Published June 9, 2008 | Version v1
Journal article

Adaptive lag synchronization in unknown stochastic chaotic neural networks with discrete and distributed time-varying delays

  • 1. College of information science and technology, Donghua University, Shanghai 201620 (China)
  • 2. Continue Education School, Shanghai Jiaotong University, Shanghai 200030 (China)

Description

In this Letter, we have dealt with the problem of lag synchronization and parameter identification for a class of chaotic neural networks with stochastic perturbation, which involve both the discrete and distributed time-varying delays. By the adaptive feedback technique, several sufficient conditions have been derived to ensure the synchronization of stochastic chaotic neural networks. Moreover, all the connection weight matrices can be estimated while the lag synchronization is achieved in mean square at the same time. The corresponding simulation results are given to show the effectiveness of the proposed method

Availability note (English)

Available from http://dx.doi.org/10.1016/j.physleta.2008.04.032

Additional details

Identifiers

DOI
10.1016/j.physleta.2008.04.032;
PII
S0375-9601(08)00564-1;

Publishing Information

Journal Title
Physics Letters. A
Journal Volume
372
Journal Issue
24
Journal Page Range
p. 4425-4433
ISSN
0375-9601
CODEN
PYLAAG

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
40046502
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
CHAOS THEORY; DISTURBANCES; FEEDBACK; NEURAL NETWORKS; SIMULATION; STOCHASTIC PROCESSES; SYNCHRONIZATION; TIME DELAY; WEIGHTING FUNCTIONS
Descriptors DEC
FUNCTIONS; MATHEMATICS

Optional Information

Copyright
Copyright (c) 2008 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.