H Control for Jumping Stochastic Cohen-Grossberg Neural Networks with Mixed Delays

This paper considers robust stability, stabilization and H ∞ control problems for jumping stochastic Cohen-Grossberg neural networks (CGNNs) with delays. A new type of mixed time delays including discrete delays and distributed delays are addressed, which fuses time-varying delays and mode-dependent delays into one whole. A delay-interval dependent control approach is presented to analyze that the closed-loop system is robust mean-square exponential stable and satisfies a prescribed H ∞ performance level based on the Linear matrix inequality (LMI) technique. Moreover, we can get the desired feedback control gain matrix by utilizing the numerically efficient Matlab LMI toolbox. Finally, two numerical examples are given to show the effectiveness of the result.