Published June 2015 | Version v1
Journal article

Synchronization criterion for linearly coupled neural networks with impulsive time window

  • 1. Southwest Univ., College of Electronic and Information Engineering, Chongqing (China)
  • 2. Texas A&M Univ. at Qatar, Doha (Qatar)
  • 3. Chongqing Normal Univ., College of Mathematics Science, Chongqing (China)

Description

Synchronization of linearly coupled neural networks with impulsive time window is one of the most challenging problems in the field of complex networks. The intrinsic property of impulse time windows is that impulse instants stochastically occur in a determined time window. In this paper, some sufficient condition in the frameworks of impulse time window and fixed impulse moments ensuring the exponential synchronization of linearly coupled neural networks are proposed by using the discretized Lyapunov function method. Moreover, some approximation algorithms are presented to compute the lower and upper bound of the impulse time window. Finally, two numerical simulations are presented to further demonstrate the validation of the proposed approach. (author)

Availability note (English)

Available from doi: https://doi.org/10.1139/cjp-2014-0331

Additional details

Identifiers

Publishing Information

Journal Title
Canadian Journal of Physics
Journal Volume
93
Journal Issue
6
Journal Page Range
p. 610-616
ISSN
0008-4204

INIS

Country of Publication
Canada
Country of Input or Organization
Canada
INIS RN
50027548
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
ARTIFICIAL INTELLIGENCE; COMPUTERIZED SIMULATION; NEURAL NETWORKS; PULSES; SYNCHRONIZATION
Descriptors DEC
SIMULATION

Optional Information

Notes
31 refs., 4 figs.