Finite-time stability of discrete fractional uncertain recurrent neural networks
This paper investigates finite-time stability of fractional uncertain difference equations with time delay. A fractional sum inequality is obtained from uncertain initial-value conditions. A delayed discrete Gronwall’s inequality is used, and sample paths are numerically illustrated. Finally, finit...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Vilnius University Press
2025-05-01
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| Series: | Nonlinear Analysis |
| Subjects: | |
| Online Access: | https://www.journals.vu.lt/nonlinear-analysis/article/view/41799 |
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| Summary: | This paper investigates finite-time stability of fractional uncertain difference equations with time delay. A fractional sum inequality is obtained from uncertain initial-value conditions. A delayed discrete Gronwall’s inequality is used, and sample paths are numerically illustrated. Finally, finite-time stability results are obtained for a fractional uncertain recurrent neural network model. It can be concluded that this paper provides an efficient tool for finite-time analysis of high-dimensional fractional uncertain systems with time delay.
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| ISSN: | 1392-5113 2335-8963 |