Stability analysis of Markovian jumping stochastic Cohen-Grossberg neural networks with mixed time delays

Abstract—In this letter, the global asymptotical stability analysis problem is considered for a class of Markovian jumping stochastic Cohen–Grossberg neural networks (CGNNs) with mixed delays including discrete delays and distributed delays. An alternative delay-dependent stability analysis result is established based on the linear matrix in-equality (LMI) technique, which can easily be checked by utilizing the numerically efficient Matlab LMI toolbox. Neither system transformation nor free-weight matrix via Newton–Leibniz formula is required. Two numerical examples are included to show the effectiveness of the result. Index Terms—Cohen–Grossberg neural networks (CGNNs), delay-de-pendent criteria, linear matrix inequality (LMI), Markovian jumping, mixed delay. I