Event-triggered fixed/preassigned time stabilization of state-dependent switching neural networks with mixed time delays

Author:

Gao Jiashu1,Han Jing2,Zhang Guodong1

Affiliation:

1. College of Mathematics and Statistics, South-Central Minzu University, Wuhan 430074, China

2. School of Information Engineering, Wuhan Business University, Wuhan 430056, China

Abstract

<abstract><p>This study employed an event-triggered control (ETC) strategy to investigate the problems of fixed-time stabilization (FTS) and preassigned-time stabilization (PTS) for state-dependent switching neural networks (SDSNNs) that involved mixed time delays. To enhance the network's generalization capability and accelerate convergence stabilization, a more intricate weight-switching mechanism was introduced, then to mitigate transmission energy consumption, this paper proposed a tailored event-triggering rule that triggered the ETC solely at predetermined time points. This rule ensured the stability of the system while effectively reducing energy consumption. Using the Lyapunov stability theory and various inequality techniques, this paper presented new results for FTS and PTS of SDSNNs. The validity of these findings was supported by conducting data simulations in two illustrative examples.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

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