Document Type
Article
Publication Date
2026
DOI
10.1080/00207721.2026.2632304
Publication Title
Scientific Reports
Pages
1-23
Abstract
In this study, a finite-time stability analysis with time delays and a leakage term is conducted on stochastic fractional-order memristive fuzzy BAM neural networks. FOMFBAMNNs are developed using set-valued map theories as well as differential inclusion. We obtained several significant adequate criteria of uniform stability in the mean square of such networks by using analytical methods and inequality approaches, such as Cauchy–Schwarz inequality and Burkholder–Davis–Gundy inequality. In addition to examining two different fractional-order derivatives between the U-layer and V-layer synchronously with fractional order, the existence, uniqueness, and stability of its equilibrium point are also shown ½ ≤ α ≤ 1. Lastly, two numerical examples are provided to demonstrate the effectiveness of the theoretical results.
Rights
© 2026 The Authors.
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Data Availability
Article states: "All data generated or analysed during this study are included in this published article."
Original Publication Citation
Kumar, J., Ali, M. S., Sanober, S., Yar, M., Alotaibi, A. M., & Ibrahim, T. F. (2026). Stochastic fractional-order memristive fuzzy bam neural networks with time delays and leakage term for finite-time stability analysis. Scientific Reports. Advance online publication. https://doi.org/10.1038/s41598-026-48581-5
Repository Citation
Kumar, J., Ali, M. S., Sanober, S., Yar, M., Alotaibi, A. M., & Ibrahim, T. F. (2026). Stochastic fractional-order memristive fuzzy bam neural networks with time delays and leakage term for finite-time stability analysis. Scientific Reports. Advance online publication. https://doi.org/10.1038/s41598-026-48581-5
ORCID
0000-0003-2533-478X (Sanober)
Included in
Applied Mathematics Commons, Artificial Intelligence and Robotics Commons, OS and Networks Commons