Dissipativity Analysis for a Class of Discrete-Time Neutral Stochastic Nonlinear Systems with Time Delay

Abstract

This paper focuses on the problem of dissipativity analysis for a class of discrete-time neutral stochastic nonlinear systems (DTNSNSs) with time delay and parameter uncertainties. Different from the existing results on this topic of neutral system, a kind of discretizing the neutral system is considered. Firstly, a sufficient condition of the dissipativity, which is dependent on the solution of the Lyapunov–Krasovskii technique and linear matrix inequalities (LMIs), is established. Moreover, the state-feedback controller is designed to guarantee the dissipative performance of the closed-loop system. The effectiveness of the theoretical results is finally demonstrated by a numerical example.

Event-Triggered Regulation for Enhanced Synchronization of Recurrent Neural Networks using Time-Varying Delay

“…In recent decades, RNNs have continued to evolve and have been effectively used in numerous fields, including artificial intelligence, management, and research [1]. To ensure the reliability of the RNN system, people have conducted extensive research on system control and stability and developed many processing approaches, such as dissipative control [2], fuzzy control [3], etc. These controlling approaches are offered to a great degree to resolve system oscillation and asynchrony issues and technological advancements.…”