Dissipative filter design for Takagi-Sugeno fuzzy neural networks

This paper proposes a novel dissipative filter for Takagi-Sugeno fuzzy Hopfield neural networks with time varying delay. This filter guarantees (Q, S, R)-a-dissipativity and is regarded as a generalization of some performance indices, such as H_∞ performance, passivity, and mixed H_∞/passivity. The linear matrix inequality (LMI) approach solving convex problem is used to obtain a gain matrix satisfying both (Q, S, R)-a-dissipativity and asymptotic stability of the error system. Some simulations are dealt with to validate the performance of the proposed method.