Exponential synchronization of fractional order fuzzy memristor neural networks with time-varying delays and impulses

Yangtao Wang; Kelin Li; Yangtao Wang; Kelin Li

doi:10.3934/mmc.2025012

Mathematical Modelling and Control

2025, Volume 5, Issue 2: 164-179. doi: 10.3934/mmc.2025012

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Research article

Exponential synchronization of fractional order fuzzy memristor neural networks with time-varying delays and impulses

Yangtao Wang ,
Kelin Li ^,

School of Mathematics and Statistics, Sichuan University of Science & Engineering, Sichuan 643000, China

Received: 19 July 2024 Revised: 06 December 2024 Accepted: 15 December 2024 Published: 22 May 2025

In this paper, the exponential synchronization of fractional order fuzzy memristor neural networks with time-varying delays and impulses is studied. In order to save cost and ensure that the control system does not jitter, two unsigned controllers are designed, and some criteria for guaranteeing exponential synchronization are given based on the differential inclusion theory and the fractional calculus theory. Finally, two numerical examples are given to verify the effectiveness of the results.
- fuzzy memristor neural network,
- exponential synchronization,
- fractional order,
- time varying delay,
- impulses
Citation: Yangtao Wang, Kelin Li. Exponential synchronization of fractional order fuzzy memristor neural networks with time-varying delays and impulses[J]. Mathematical Modelling and Control, 2025, 5(2): 164-179. doi: 10.3934/mmc.2025012

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Abstract

In this paper, the exponential synchronization of fractional order fuzzy memristor neural networks with time-varying delays and impulses is studied. In order to save cost and ensure that the control system does not jitter, two unsigned controllers are designed, and some criteria for guaranteeing exponential synchronization are given based on the differential inclusion theory and the fractional calculus theory. Finally, two numerical examples are given to verify the effectiveness of the results.

References

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