Finite-time adaptive synchronization of coupled uncertain neural networks via intermittent control
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 f...
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Veröffentlicht in: | Physica A 2022-06, Vol.596, p.127107, Article 127107 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 0378-4371 1873-2119 |
DOI: | 10.1016/j.physa.2022.127107 |