Hybrid event-triggered synchronization control of delayed chaotic neural networks against communication delay and random data loss

• Published in: Chaos, solitons and fractals Vol. 172; p. 113535
• Main Authors: Gao, Zifan, Zhang, Dawei, Zhu, Shuqian
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2023
• Subjects: Binary quadratic convex lemma; Chaotic synchronization; Delayed chaotic neural networks; Hybrid event-triggered communication; Random data loss; Hybrid event-triggered communication; Chaotic synchronization; Random data loss; Binary quadratic convex lemma; Delayed chaotic neural networks
• ISSN: 0960-0779; 1873-2887
• DOI: 10.1016/j.chaos.2023.113535

This paper investigates the network-based synchronization control of delayed chaotic neural networks. A new hybrid event-triggered communication scheme, which consists of fixed and dynamic triggering conditions, is presented to handle the random loss of triggered sampled-data. Under this scheme, a quantitative relation between the allowable data loss probability and the fixed triggering interval can be revealed. The synchronous error system is modeled by a multi-constrained system affected by nonlinear terms, piecewise input delay, stochastic update input and reset states. By using the boundary information and interrelation of both communication delay and input delay, a binary quadratic convex lemma and a tailored discontinuous augmented Lyapunov-Krasovskii functional approach are proposed to exploit delay-dependent synchronization criteria with less conservatism. Simulation results are provided for checking the merits of the obtained criteria.