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-2014-0331Additional 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.