Fixed-Time Stability for Discontinuous Uncertain Inertial Neural Networks With Time-Varying Delays
研究了一类参数不确定且带时滞的不连续惯性神经网络的固定时间稳定性问题，通过变量变换和微分包含理论建立驱动-响应系统，设计了不连续控制策略并给出新的延迟依赖判据和稳定时间估计。
In this article, a class of discontinuous inertial neural networks (DINNs) with parameter uncertainties and time delays is studied. The main aim is to investigate the new fixed-time stability (FTS). In order to achieve the targets, first, by introducing the generalized variable transformation and differential inclusions theory, two kinds of drive–response differential inclusion systems are established. Based on the definition of FTS and inequality technologies, by constructing the Lyapunov–Krasovskii functional (LKF), whose derivative is allowed to be indefinite, new delay-dependent criteria shown by some simple inequalities are derived for the purposing of achieving the FTS based on the designed discontinuous control strategies. Moreover, the new settling time (ST) is given. Compared to the previous stability results on INNs, the results established and the approaches applied are absolutely new. Finally, examples are given to show the effectiveness of the established results.