Title of article :
Global robust stability criteria of stochastic Cohen–Grossberg neural networks with discrete and distributed time-varying delays
Author/Authors :
Su، نويسنده , , Weiwei and Chen، نويسنده , , Yiming، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Pages :
9
From page :
520
To page :
528
Abstract :
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 by 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.
Keywords :
Stochastic Cohen–Grossberg neural networks , Delay-dependent robust stability , Discrete and distributed time-varying delays , Norm-bounded uncertainties
Journal title :
Communications in Nonlinear Science and Numerical Simulation
Serial Year :
2009
Journal title :
Communications in Nonlinear Science and Numerical Simulation
Record number :
1534026
Link To Document :
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