Global asymptotic stability of stochastic Cohen–Grossberg-type BAM neural networks with mixed delays: An LMI approach

摘要

In this paper, we consider the stochastic Cohen–Grossberg-type BAM neural networks with mixed delays. By utilizing the Lyapunov–Krasovskii functional and the linear matrix inequality (LMI) approach, some sufficient LMI-based conditions are obtained to guarantee the global asymptotic stability of stochastic Cohen–Grossberg-type BAM neural networks with mixed delays. These conditions can be easily checked via the MATLAB LMI toolbox. Moreover, the obtained results extend and improve the earlier publications. Finally, a numerical example is provided to demonstrate the low conservatism and effectiveness of the proposed LMI conditions.