Strict dissipativity synchronization for delayed static neural networks: An event-triggered scheme

This article addresses the investigation of strict dissipativity synchronization for a class of static neural networks under an event-triggered scheme. An event-triggered scheme is recommended, it can upgrade the exhibition of system dynamics and diminishes the network communication burden at the same time. Firstly, an appropriate Lyapunov-Krasovskii functional (LKF) with double and triple integral terms with the details on both lower and upper bounds of the delay is completely designed. Secondly, under the single and double Auxiliary function-based integral inequalities (SAFBII and DAFBII, respectively) and generalized free weight matrix approach, a new class of delay-dependent adequate condition is proposed, so that the error system is (Q, S, R) -gamma- strict dissipative. A resilient distributed event-triggered control scheme is developed by this criterion in terms of linear matrix inequalities (LMIs). At last, simulation examples are provided to demonstrate the performance of the derived results. (C) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This article investigates strict dissipativity synchronization for a class of static neural networks under an event-triggered scheme, proposing a design scheme and sufficient conditions based on LMIs, and demonstrating the performance of the derived results through simulation examples.