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Zbl 1221.37196
Su, Weiwei; Chen, Yiming
Global robust stability criteria of stochastic Cohen-Grossberg neural networks with discrete and distributed time-varying delays. (English)
[J] Commun. Nonlinear Sci. Numer. Simul. 14, No. 2, 520-528 (2009). ISSN 1007-5704

Summary: The paper is concerned with the problem of robust asymptotic stability analysis of stochastic Cohen-Grossberg neural networks with discrete and distributed time-varying delays. Based on the Lyapunov stability theory and linear matrix inequality (LMI) technology, some sufficient conditions are derived to ensure the global robust convergence of the equilibrium point. The proposed conditions can be checked easily with the LMI Control Toolbox in Matlab. Furthermore, all the results are obtained under mild conditions, assuming neither differentiability nor strict monotonicity for activation function. A numerical example is given to demonstrate the effectiveness of our results.

MSC 2000:: *37N25 Dynamical systems in biology
34K20 Stability theory of functional-differential equations
34F05 ODE with randomness
60H10 Stochastic ordinary differential equations
62M45 Neural nets and related approaches
92B20 General theory of neural networks

Keywords: stochastic Cohen-Grossberg neural networks; delay-dependent robust stability; discrete and distributed time-varying delays; norm-bounded uncertainties

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Zentralblatt MATH Berlin [Germany]