Dissipative criteria for Takagi–Sugeno fuzzy Markovian jumping neural networks with impulsive perturbations using delay partitioning approach

Abstract

Abstract In this work, we investigate the result of dissipative analysis for Takagi–Sugeno fuzzy Markovian jumping neural networks with impulsive perturbations via delay partition approach. By using the Lyapunov–Krasovskii functional and delay partition approach, we derive a set of delay-dependent sufficient criteria for obtaining the required results. Furthermore, we restate the obtained sufficient conditions in the form of linear matrix inequalities (LMIs), which can be checked by the standard MATLAB LMI tool box. The main advantage of this work is reduced conservatism, which is mainly based on the delay partition approach. Finally, we provide numerical examples with simulations to demonstrate the applicability of the proposed method.

Keywords

• Dissipativity
• Markovian jumping neural network
• Impulses
• Lyapunov–Krasovskii functional
• Linear matrix inequality