Finite Time Stability of Cohen-Grossberg Neural Network with Time-Varying Delays

摘要

This paper considers the problem of finite time stability (FTS) of the Cohen-Grossberg neural networks with or without delay. Based on the Lyapunov function and linear matrix inequality (LMI) technique, some delay-dependent and delay-independent criterions are derived to guarantee finite-time stability. Finally, one example is given to demonstrate the validity of the proposed methodology and to show the differences between globally exponential stability and finite-time stability.