Exponential stability analysis for delayed stochastic Cohen-Grossberg neural network

DOI

10.2991/ijcis.2010.3.1.9How to use a DOI?

Keywords

Exponential stability, Cohen-Grossberg neural networks, Lyapunov method, Razumikhin-type theorem, Brownian motion

Abstract

In this paper, the exponential stability problems are addressed for a class of delayed Cohen-Grossberg neural networks which are also perturbed by some stochastic noises. By employing the Lyapunov method, stochastic analysis and some inequality techniques, sufficient conditions are acquired for checking the pth(p > 1) and the 1st moment exponential stability of the network. Finally, One example is given to show the effectiveness of the proposed results.

Copyright

© 2010, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Guanjun Wang
AU  - Jinling Liang
PY  - 2010
DA  - 2010/04/01
TI  - Exponential stability analysis for delayed stochastic Cohen-Grossberg neural network
JO  - International Journal of Computational Intelligence Systems
SP  - 96
EP  - 102
VL  - 3
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2010.3.1.9
DO  - 10.2991/ijcis.2010.3.1.9
ID  - Wang2010
ER  -