Finite-time adaptive synchronization of coupled uncertain neural networks via intermittent control

Wenjia Zhou, Yuanfa Hu, Xiaoyang Liu and Jinde Cao

Physica A: Statistical Mechanics and its Applications, 2022, vol. 596, issue C

Abstract: This paper considers the finite-time synchronization (FTS) of coupled neural networks (CNNs) with parameter uncertainties. Based on the adaptive periodically intermittent control method and the finite-time stability theory, some sufficient conditions are derived to achieve synchronization within a finite time. Both the models of CNNs with/without delays are considered and the corresponding upper-bounds of synchronization time are estimated as well. Finally, two illustrative examples are presented to demonstrate the effectiveness and applicability of the theoretical results.

Keywords: Coupled neural networks; Finite-time synchronization; Adaptive intermittent control (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:596:y:2022:i:c:s037843712200139x

DOI: 10.1016/j.physa.2022.127107

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