Asymptotical Mean Square Stability of Cohen-Grossberg Neural Networks with Random Delay

Enwen Zhu, Hanjun Zhang, Jiezhong Zou
2010 Journal of Inequalities and Applications  
The asymptotical mean-square stability analysis problem is considered for a class of Cohen-Grossberg neural networks CGNNs with random delay. The evolution of the delay is modeled by a continuous-time homogeneous Markov process with a finite number of states. The main purpose of this paper is to establish easily verifiable conditions under which the random delayed Cohen-Grossberg neural network is asymptotical mean-square stability. By employing Lyapunov-Krasovskii functionals and conducting
more » ... chastic analysis, a linear matrix inequality LMI approach is developed to derive the criteria for the asymptotical mean-square stability, which can be readily checked by using some standard numerical packages such as the Matlab LMI Toolbox. A numerical example is exploited to show the usefulness of the derived LMI-based stability conditions.
doi:10.1155/2010/247587 fatcat:uxnr4oht2jfb3pzmuasklanbie