Mean square exponential stability of stochastic fuzzy delayed Cohen–Grossberg neural networks with expectations in the coefficients

In this paper, we consider a class of stochastic fuzzy Cohen–Grossberg neural networks with time-varying delays. Different from the previous literature, we introduce expectations into coefficients of the model. Under some reasonable conditions, we show that the trivial solution of the suggested system is exponentially stable in the mean square. Finally, an example is given to illustrate the effectiveness of the theoretical results.