Dynamical behaviors of impulsive reaction-diffusion Cohen-Grossberg neural network with delays

In this paper, an impulsive reaction-diffusion Cohen-Grossberg neural network with delays and Neumann boundary condition is considered. By utilizing Poincare inequality, constructing suitable Lyapunov functional method, some new sufficient conditions are obtained to ensure the global exponential stability of the equilibrium point. The obtained sufficient conditions depend on the reaction-diffusion terms. A comparison between our results and the previous results shows that diffusion terms can be used to exponentially stabilize some reaction-diffusion neural networks with delays and the previous results have been improved.

[1]  Xinzhi Liu,et al.  Impulsive Stabilization of High-Order Hopfield-Type Neural Networks With Time-Varying Delays , 2008, IEEE Transactions on Neural Networks.

[2]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[3]  Jianlong Qiu,et al.  Exponential stability of impulsive neural networks with time-varying delays and reaction-diffusion terms , 2007, Neurocomputing.

[4]  Qinghua Zhou,et al.  Global Exponential Stability for a Class of impulsive integro-Differential equation , 2008, Int. J. Bifurc. Chaos.

[5]  Qiankun Song,et al.  Global exponential robust stability of Cohen-Grossberg neural network with time-varying delays and reaction-diffusion terms , 2006, J. Frankl. Inst..

[6]  S. Arik,et al.  Global stability analysis of Cohen–Grossberg neural networks with time varying delays , 2005 .

[7]  Jianhua Sun,et al.  Exponential stability of reaction–diffusion generalized Cohen–Grossberg neural networks with time-varying delays , 2007 .

[8]  J. Ruan,et al.  Global stability analysis of impulsive Cohen–Grossberg neural networks with delay , 2005 .

[9]  Kwok-Wo Wong,et al.  Criteria for exponential stability of Cohen-Grossberg neural networks , 2004, Neural Networks.

[10]  Kunlun Wang,et al.  Dynamical behaviors of Cohen-Grossberg neural networks with delays and reaction-diffusion terms , 2006, Neurocomputing.

[11]  Jinde Cao,et al.  Boundedness and stability for Cohen–Grossberg neural network with time-varying delays☆ , 2004 .

[12]  J. Ruan,et al.  Global dynamic analysis of general Cohen–Grossberg neural networks with impulse , 2007 .

[13]  X. Zou,et al.  Harmless delays in Cohen–Grossberg neural networks ☆ , 2002 .

[14]  Daoyi Xu,et al.  Impulsive effects on stability of Cohen-Grossberg neural networks with variable delays , 2006, Appl. Math. Comput..

[15]  Jinde Cao,et al.  Global exponential stability of reaction–diffusion recurrent neural networks with time-varying delays , 2003 .

[17]  Min Wu,et al.  LMI-based stability criteria for neural networks with multiple time-varying delays , 2005 .

[18]  Chuandong Li,et al.  Stability of Cohen-Grossberg neural networks with unbounded distributed delays , 2007 .

[19]  Kelin Li,et al.  Exponential stability of impulsive Cohen-Grossberg neural networks with time-varying delays and reaction-diffusion terms , 2008, Neurocomputing.

[20]  Richard E. Mortensen,et al.  Infinite-Dimensional Dynamical Systems in Mechanics and Physics (Roger Temam) , 1991, SIAM Rev..

[21]  Qinghua Zhou Global exponential stability of BAM neural networks with distributed delays and impulses , 2009 .

[22]  Jigen Peng,et al.  Delay-independent criteria for exponential stability of generalized Cohen-Grossberg neural networks with discrete delays , 2006 .

[23]  Jinde Cao,et al.  Stability analysis of Cohen-Grossberg neural network with both time-varying and continuously distributed delays , 2006 .

[24]  Jiye Zhang,et al.  Global exponential stability of Cohen–Grossberg neural networks with variable delays☆ , 2005 .

[25]  Jinde Cao,et al.  Global exponential stability and periodicity of recurrent neural networks with time delays , 2005, IEEE Transactions on Circuits and Systems I: Regular Papers.

[26]  Xuyang Lou,et al.  Boundedness and exponential stability for nonautonomous cellular neural networks with reaction–diffusion terms , 2007 .