Synchronization for Delayed Fractional-Order Memristive Neural Networks Based on Intermittent-Hold Control with Application in Secure Communication

This article investigates the dynamic behaviors of delayed fractional-order memristive fuzzy cellular neural networks via the Lyapunov method. To address the delay terms of fractional-order systems, a novel lemma is provided to make the solutions of the systems exponentially stable. Furthermore, two new intermittent-hold controllers are designed to improve the robustness of the system and reduce the cost of the controller. One intermittent-hold controller is based on the feedback control strategy, while the other one integrates an adaptive control strategy. Moreover, two crucial theorems are derived from the proposed lemma and controllers, guaranteeing the exponential synchronization between drive and response systems. Finally, the superior performance of the controllers in achieving exponential synchronization is demonstrated through simulations.

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Publication Details

Journal
Fractal and Fractional
Published
2024-08-30
DOI
https://doi.org/10.3390/fractalfract8090519
Citations
4
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
1.40

Funders

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article

Synchronization for Delayed Fractional-Order Memristive Neural Networks Based on Intermittent-Hold Control with Application in Secure Communication

Xueqi Yao, Jingxi Shi, Yuanhua Du, Shouming Zhong
4 citations
Fractal and Fractional
Neural Networks Stability and Synchronization
1.40
article

Synchronization for Delayed Fractional-Order Memristive Neural Networks Based on Intermittent-Hold Control with Application in Secure Communication

Xueqi Yao, Jingxi Shi, Yuanhua Du, Shouming Zhong
article en
4 citations

Abstract

This article investigates the dynamic behaviors of delayed fractional-order memristive fuzzy cellular neural networks via the Lyapunov method. To address the delay terms of fractional-order systems, a novel lemma is provided to make the solutions of the systems exponentially stable. Furthermore, two new intermittent-hold controllers are designed to improve the robustness of the system and reduce the cost of the controller. One intermittent-hold controller is based on the feedback control strategy, while the other one integrates an adaptive control strategy. Moreover, two crucial theorems are derived from the proposed lemma and controllers, guaranteeing the exponential synchronization between drive and response systems. Finally, the superior performance of the controllers in achieving exponential synchronization is demonstrated through simulations.

Fractal and FractionalVol. 8(9)
Xihua University (CN), University of Electronic Science and Technology of China (CN), Chengdu University of Information Technology (CN)
Chengdu University of Information Technology, National Natural Science Foundation of China, Chengdu University, Natural Science Foundation of Sichuan Province
Openalex Percentile: Top 17%
Neural Networks Stability and Synchronization
1.40
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Synchronization for Delayed Fractional-Order Memristive Neural Networks Based on Intermittent-Hold Control with Application in Secure Communication — Xueqi Yao, Jingxi Shi, et al. · Fractal and Fractional (2024) | TGRS Research Map | TGRS