Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

September 2014, Vol. 26, No. 9, Pages 2005-2024
(doi: 10.1162/NECO_a_00629)
@ 2014 Massachusetts Institute of Technology
Synchronization of Stochastic Competitive Neural Networks with Different Timescales and Reaction-Diffusion Terms
Article PDF (661.93 KB)
Abstract

We propose a feedback controller for the synchronization of stochastic competitive neural networks with different timescales and reaction-diffusion terms. By constructing a proper Lyapunov-Krasovskii functional, as well as employing stochastic analysis theory, the LaShall-type invariance principle for stochastic differential delay equations, and a linear matrix inequality (LMI) technique, a feedback controller is designed to achieve the asymptotical synchronization of coupled stochastic competitive neural networks. A simulation example is given to show the effectiveness of the theoretical results.