Robust Stability of Fractional Order Memristive BAM Neural Networks with Mixed and Additive Time Varying Delays

Xiuping Han; M. Hymavathi; Sumaya Sanober; Bhawna Dhupia; M. Syed Ali

doi:10.3390/fractalfract6020062

Fractal and Fractional (Jan 2022)

Robust Stability of Fractional Order Memristive BAM Neural Networks with Mixed and Additive Time Varying Delays

Xiuping Han,
M. Hymavathi,
Sumaya Sanober,
Bhawna Dhupia,
M. Syed Ali

Affiliations

Xiuping Han: School of Mathematics and Statistics, Shandong Normal University, Jinan 250014, China
M. Hymavathi: Department of Mathematics, Thiruvalluvar University, Vellore 632115, India
Sumaya Sanober: Department of Computer Science, College of Arts and Science, Prince Sattam Bin Abdulaziz University, Wadi Aldawaser 11991, Saudi Arabia
Bhawna Dhupia: Department of Computer Science, College of Arts and Science, Prince Sattam Bin Abdulaziz University, Wadi Aldawaser 11991, Saudi Arabia
M. Syed Ali: Department of Mathematics, Thiruvalluvar University, Vellore 632115, India

DOI: https://doi.org/10.3390/fractalfract6020062
Journal volume & issue: Vol. 6, no. 2
p. 62

Abstract

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This paper is concerned with the problem of the robust stability of fractional-order memristive bidirectional associative memory (BAM) neural networks. Based on Lyapunov theory, fractional-order differential inequalities and linear matrix inequalities (LMI) are applied to obtain a robust asymptotical stability. Finally, numerical examples are presented.

Published in Fractal and Fractional

ISSN: 2504-3110 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science: Physics: Heat: Thermodynamics; Science: Mathematics: Analysis
Website: http://www.mdpi.com/journal/fractalfract

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