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

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.

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Publication Details

Journal
Mathematical Modelling and Control
Published
2025-01-01
DOI
https://doi.org/10.3934/mmc.2025012
Citations
15
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
22.31
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article

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

Yangtao Wang, Kelin Li
15 citations
Mathematical Modelling and Control
Neural Networks Stability and Synchronization
22.31
article

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

Yangtao Wang, Kelin Li
article en
15 citations

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.

Mathematical Modelling and ControlVol. 5(2)
Sichuan University of Science and Engineering (CN)
Affordable and clean energy
Openalex Percentile: Top 1%
Neural Networks Stability and Synchronization
22.31
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