Work

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

Year: 2024

Type: article

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.

Source: Fractal and Fractional

DOI: 10.3390/fractalfract8090519

Authors: Xueqi Yao, Jingxi Shi, Shouming Zhong, Yuanhua Du

Institutions: Chengdu University of Information Technology, Xihua University, University of Electronic Science and Technology of China

Language: English

Topic: Neural Networks Stability and Synchronization

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,069

Funders: Chengdu University of Information Technology, National Natural Science Foundation of China, Chengdu University, Natural Science Foundation of Sichuan Province