Exponential periodicity and stability of delayed neural networks
Mathematics and Computers in Simulation
Journal of Computational and Applied Mathematics
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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.