Exponential dissipativity analysis of discrete-time switched memristive neural networks with actuator saturation via quasi-time-dependent control

Abstract

The dissipativity of discrete-time switched memristive neural networks with actuator saturation is considered in this paper. By constructing a quasi-time-dependent Lyapunov function, sufficient conditions are obtained to guarantee the exponential stability and exponential dissipativity for the closed-loop system with mode-dependent average dwell time switching. Furthermore, the exponential H∞ performance of discrete-time switched memristive neural networks is also analyzed, while the quasi-time-dependent controller and observer gains of the desired exponential dissipative and H∞ performance can be calculated from linear matrix inequalities. Finally, the effectiveness of theoretical results is illustrated through the numerical examples.