New Finite-Time and Global Mittag-Leffler Stability Criteria for Fractional-Order BAM Neural Networks with S-Type Distributed Delays

This paper investigates the stability analysis of a class of fractional-order bidirectional associative memory neural networks (FOBAMNNs) with S-type distributed delays, which incorporating both discrete and distributed delays through a Lebesgue-Stieltjes integral. Leveraging the properties of Riemann-Liouville fractional-order derivatives and integrals, along with the additivity of integration intervals and initial conditions, we transform fractional-order integrals of the state function involving S-type distributed delays into equivalent integrals without such delays. Utilizing the theory of contractive mapping and the Bellman-Gronwall inequality, the finite-time stability (FTS) and global Mittag-Leffler stability (GLMS) criteria are established when certain conditions were satisfied. Moreover, the two distinct types of stability, FTS and GMLS, in FOBAMNNs are governed by appropriate parameters, complementing each other and laying a new foundation for advancing research and practical applications in neural networks. Furthermore, the validity and practical applicability of the theoretical results are demonstrated through two illustrative numerical simulation examples.

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Publication Details

Journal
Neural Processing Letters
Published
2025-12-17
DOI
https://doi.org/10.1007/s11063-025-11813-2
Primary Topic
Neural Networks Stability and Synchronization
Type
article
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article

New Finite-Time and Global Mittag-Leffler Stability Criteria for Fractional-Order BAM Neural Networks with S-Type Distributed Delays

Wei Liu, Qinghua Zuo
Neural Processing Letters
Neural Networks Stability and Synchronization
article

New Finite-Time and Global Mittag-Leffler Stability Criteria for Fractional-Order BAM Neural Networks with S-Type Distributed Delays

Wei Liu, Qinghua Zuo
article en

Abstract

This paper investigates the stability analysis of a class of fractional-order bidirectional associative memory neural networks (FOBAMNNs) with S-type distributed delays, which incorporating both discrete and distributed delays through a Lebesgue-Stieltjes integral. Leveraging the properties of Riemann-Liouville fractional-order derivatives and integrals, along with the additivity of integration intervals and initial conditions, we transform fractional-order integrals of the state function involving S-type distributed delays into equivalent integrals without such delays. Utilizing the theory of contractive mapping and the Bellman-Gronwall inequality, the finite-time stability (FTS) and global Mittag-Leffler stability (GLMS) criteria are established when certain conditions were satisfied. Moreover, the two distinct types of stability, FTS and GMLS, in FOBAMNNs are governed by appropriate parameters, complementing each other and laying a new foundation for advancing research and practical applications in neural networks. Furthermore, the validity and practical applicability of the theoretical results are demonstrated through two illustrative numerical simulation examples.

Neural Processing LettersVol. 58(1)
Shaoxing University (CN)
Openalex Percentile: Top 54%
Neural Networks Stability and Synchronization
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