Passive and exponential filter design for fuzzy neural networks

This paper proposes a new passive and exponential filter for Takagi-Sugeno fuzzy Hopfield neural networks, with time delay and external disturbance. Based on the Lyapunov-Krasovskii stability theory, Jensen’s inequality, and linear matrix inequality (LMI), a new delay-dependent criterion is proposed such that the filtering error system becomes exponentially stable and passive from the external disturbance to the output error. The proposed filter can be obtained by solving the LMI, which can be easily facilitated using standard numerical packages. Two numerical examples are given to illustrate the effectiveness of the proposed filter.