Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacks
This article investigates the finite-time decentralized event-triggered feedback control problem for generalized neural networks (GNNs) with mixed interval time-varying delays and cyber-attacks. A decentralized event-triggered method reduces the network transmission load and decides whether sensor m...
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| Format: | Article |
| Language: | English |
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AIMS Press
2023-07-01
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| Series: | AIMS Mathematics |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/math.20231136?viewType=HTML |
| _version_ | 1797771633393401856 |
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| author | Chantapish Zamart Thongchai Botmart Wajaree Weera Prem Junsawang |
| author_facet | Chantapish Zamart Thongchai Botmart Wajaree Weera Prem Junsawang |
| author_sort | Chantapish Zamart |
| collection | DOAJ |
| description | This article investigates the finite-time decentralized event-triggered feedback control problem for generalized neural networks (GNNs) with mixed interval time-varying delays and cyber-attacks. A decentralized event-triggered method reduces the network transmission load and decides whether sensor measurements should be sent out. The cyber-attacks that occur at random are described employing Bernoulli distributed variables. By the Lyapunov-Krasovskii stability theory, we apply an integral inequality with an exponential function to estimate the derivative of the Lyapunov-Krasovskii functionals (LKFs). We present new sufficient conditions in the form of linear matrix inequalities. The main objective of this research is to investigate the stochastic finite-time boundedness of GNNs with mixed interval time-varying delays and cyber-attacks by providing a decentralized event-triggered method and feedback controller. Finally, a numerical example is constructed to demonstrate the effectiveness and advantages of the provided control scheme. |
| first_indexed | 2024-03-12T21:40:25Z |
| format | Article |
| id | doaj.art-70124582822f4563b0c89f1d09821c4d |
| institution | Directory Open Access Journal |
| issn | 2473-6988 |
| language | English |
| last_indexed | 2024-03-12T21:40:25Z |
| publishDate | 2023-07-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Mathematics |
| spelling | doaj.art-70124582822f4563b0c89f1d09821c4d2023-07-27T01:26:27ZengAIMS PressAIMS Mathematics2473-69882023-07-0189222742230010.3934/math.20231136Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacksChantapish Zamart0Thongchai Botmart1Wajaree Weera2Prem Junsawang3 1. Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand 1. Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand1. Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand2. Department of Statistics, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, ThailandThis article investigates the finite-time decentralized event-triggered feedback control problem for generalized neural networks (GNNs) with mixed interval time-varying delays and cyber-attacks. A decentralized event-triggered method reduces the network transmission load and decides whether sensor measurements should be sent out. The cyber-attacks that occur at random are described employing Bernoulli distributed variables. By the Lyapunov-Krasovskii stability theory, we apply an integral inequality with an exponential function to estimate the derivative of the Lyapunov-Krasovskii functionals (LKFs). We present new sufficient conditions in the form of linear matrix inequalities. The main objective of this research is to investigate the stochastic finite-time boundedness of GNNs with mixed interval time-varying delays and cyber-attacks by providing a decentralized event-triggered method and feedback controller. Finally, a numerical example is constructed to demonstrate the effectiveness and advantages of the provided control scheme.https://www.aimspress.com/article/doi/10.3934/math.20231136?viewType=HTMLgeneralized neural networksfinite-time stabilitytime-varying delaysfeedback controlcyber-attacksdecentralized event-triggered scheme |
| spellingShingle | Chantapish Zamart Thongchai Botmart Wajaree Weera Prem Junsawang Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacks AIMS Mathematics generalized neural networks finite-time stability time-varying delays feedback control cyber-attacks decentralized event-triggered scheme |
| title | Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacks |
| title_full | Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacks |
| title_fullStr | Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacks |
| title_full_unstemmed | Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacks |
| title_short | Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacks |
| title_sort | finite time decentralized event triggered feedback control for generalized neural networks with mixed interval time varying delays and cyber attacks |
| topic | generalized neural networks finite-time stability time-varying delays feedback control cyber-attacks decentralized event-triggered scheme |
| url | https://www.aimspress.com/article/doi/10.3934/math.20231136?viewType=HTML |
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