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

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.