Neural Networks2022,Vol.14512.DOI:10.1016/j.neunet.2021.10.027

Fractional-order discontinuous systems with indefinite LKFs: An application to fractional-order neural networks with time delays

Udhayakumar K. Rihan F.A. Rakkiyappan R. Cao J.
Neural Networks2022,Vol.14512.DOI:10.1016/j.neunet.2021.10.027

Fractional-order discontinuous systems with indefinite LKFs: An application to fractional-order neural networks with time delays

Udhayakumar K. 1Rihan F.A. 2Rakkiyappan R. 1Cao J.3
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作者信息

  • 1. Department of Mathematics Bharathiar University
  • 2. Department of Mathematical Sciences College of Science United Arab Emirates University
  • 3. School of Mathematics Southeast University
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Abstract

? 2021 Elsevier LtdIn this article, we discuss bipartite fixed-time synchronization for fractional-order signed neural networks with discontinuous activation patterns. The Filippov multi-map is used to convert the fixed-time stability of the fractional-order general solution into the zero solution of the fractional-order differential inclusions. On the Caputo fractional-order derivative, Lyapunov-Krasovskii functional is proved to possess the indefinite fractional derivatives for fixed-time stability of fragmentary discontinuous systems. Furthermore, the fixed-time stability of the fractional-order discontinuous system is achieved as well as an estimate of the new settling time. The discontinuous controller is designed for the delayed fractional-order discontinuous signed neural networks with antagonistic interactions and new conditions for permanent fixed-time synchronization of these networks with antagonistic interactions are also provided, as well as the settling time for permanent fixed-time synchronization. Two numerical simulation results are presented to demonstrate the effectiveness of the main results

Key words

Discontinuous activations/Fixed-time synchronization/Fractional-order/Lyapunov-Krasovskii functional/Signed neural networks

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出版年

2022
Neural Networks

Neural Networks

EISCI
ISSN:0893-6080
被引量28
参考文献量47
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