New dissipativity condition of stochastic fuzzy neural networks with discrete and distributed time-varying delays

This paper deals with the dissipativity problem for interval type-2 (IT2) stochastic fuzzy neural networks subject to discrete and distributed time-varying delays. Firstly, a new type of IT2 stochastic fuzzy neural network with parameter uncertainties is proposed. The parameter uncertainties can be efficiently tackled by lower and upper membership functions and relative weighting functions. Secondly, according to Ito differential formula and stochastic analysis scheme, a new dissipativity condition is obtained. In the design process, the dissipativity condition can be transformed to convex optimization problem. Finally, a numerical example is proposed to reveal the feasibility of the proposed approach.

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