Lou Xuyang, Cui Baotong
Research Center of Control Science and Engineering, Southern Yangtze University, Jiangsu 214122, PR China.
Int J Neural Syst. 2006 Dec;16(6):435-43. doi: 10.1142/S0129065706000834.
In this paper, the problem of global robust exponential stabilization for a class of neural networks with reaction-diffusion terms and time-varying delays which covers the Hopfield neural networks and cellular neural networks is investigated. A feedback control gain matrix is derived to achieve the global robust exponential stabilization of the neural networks by using the Lyapunov stability theory, and the stabilization condition can be verified if a certain Hamiltonian matrix with no eigenvalues on the imaginary axis. This condition can avoid solving an algebraic Riccati equation. Finally, a numerical simulation illustrates the effectiveness of the results.
