New Criteria for Robust Stability of Cohen-Grossberg Neural Networks with Multiple Delays
Huanxin Guan · Dianzi xuebao · 2007
Global robust stability of a class of Cohen-Grossberg neural networks with multiple delays and parameter perturbations is analyzed.By way of constructing a suitable Lyapunov functional,the criteria expressed by the form of linear matrix inequality(LMI) are given for the global robust stability of equilibrium point.In addition,all results are established without assuming any symmetry of the interconnecting matrix,and the differentiability and monotonicity of activation functions.The simulation samples have proved the effectiveness of the conclusion.