Journal
CHAOS SOLITONS & FRACTALS
Volume 172, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2023.113535
Keywords
Chaotic synchronization; Delayed chaotic neural networks; Hybrid event-triggered communication; Random data loss; Binary quadratic convex lemma
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This paper investigates the network-based synchronization control of delayed chaotic neural networks. A new hybrid event-triggered communication scheme 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 proposed criteria exploit delay-dependent synchronization with less conservatism by using the boundary information and interrelation of both communication delay and input delay.
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.
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