Quasi-Mittag-Leffler Projective Synchronization of Delayed Chaotic Fractional Order Neural Network with Mismatched Parameters Article Swipe
Xin Sui
,
Yongqing Yang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/fractalfract9060379
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/fractalfract9060379
This paper investigates the synchronization control problem for delayed fractional-order neural networks (DFONNs) with mismatched parameters. A novel synchronization behavior termed quasi-Mittag-Leffler projective synchronization (QMLPS) is studied. The core contribution of this work lies in the following: (1) The time delay and mismatched parameters between driven and response systems are considered, which is more general. Both static controllers and adaptive controllers are designed to synchronize the DFONNs. (2) The synchronization errors are estimated, and the rate of convergence is clarified description. By using the Lyapunov stability theory and some significant fractional-order differential inequalities, some sufficient conditions for DFONNs are derived under two kinds of control methods; furthermore, the bound of synchronization errors is estimated by the Mittag-Leffler function. Quantitative numerical simulations have demonstrated the superiority of our controller. Compared to existing results, the QMLPS introduced in this paper is more general, incorporating many existing synchronization concepts. The numerical simulation section verifies the effectiveness of the theoretical results, providing several types of synchronization behaviors of the controlled system under both mismatched and matched parameter conditions, and it also demonstrates the accuracy of the theoretical estimation of synchronization error bounds.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/fractalfract9060379
- https://www.mdpi.com/2504-3110/9/6/379/pdf?version=1750139006
- OA Status
- gold
- Cited By
- 3
- References
- 33
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411350251
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411350251Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/fractalfract9060379Digital Object Identifier
- Title
-
Quasi-Mittag-Leffler Projective Synchronization of Delayed Chaotic Fractional Order Neural Network with Mismatched ParametersWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-06-15Full publication date if available
- Authors
-
Xin Sui, Yongqing YangList of authors in order
- Landing page
-
https://doi.org/10.3390/fractalfract9060379Publisher landing page
- PDF URL
-
https://www.mdpi.com/2504-3110/9/6/379/pdf?version=1750139006Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2504-3110/9/6/379/pdf?version=1750139006Direct OA link when available
- Concepts
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Chaotic, Projective test, Mathematics, Artificial neural network, Synchronization (alternating current), Order (exchange), Topology (electrical circuits), Computer science, Pure mathematics, Artificial intelligence, Combinatorics, Finance, EconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3Per-year citation counts (last 5 years)
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33Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.termed | 20 |
| abstract_inverted_index.theory | 86 |
| abstract_inverted_index.(QMLPS) | 24 |
| abstract_inverted_index.DFONNs. | 66 |
| abstract_inverted_index.between | 44 |
| abstract_inverted_index.bounds. | 187 |
| abstract_inverted_index.control | 5, 104 |
| abstract_inverted_index.delayed | 8 |
| abstract_inverted_index.derived | 99 |
| abstract_inverted_index.matched | 171 |
| abstract_inverted_index.problem | 6 |
| abstract_inverted_index.section | 149 |
| abstract_inverted_index.several | 158 |
| abstract_inverted_index.systems | 48 |
| abstract_inverted_index.(DFONNs) | 12 |
| abstract_inverted_index.Compared | 128 |
| abstract_inverted_index.Lyapunov | 84 |
| abstract_inverted_index.accuracy | 179 |
| abstract_inverted_index.adaptive | 59 |
| abstract_inverted_index.behavior | 19 |
| abstract_inverted_index.designed | 62 |
| abstract_inverted_index.existing | 130, 143 |
| abstract_inverted_index.general, | 140 |
| abstract_inverted_index.general. | 54 |
| abstract_inverted_index.methods; | 105 |
| abstract_inverted_index.networks | 11 |
| abstract_inverted_index.response | 47 |
| abstract_inverted_index.results, | 131, 156 |
| abstract_inverted_index.studied. | 26 |
| abstract_inverted_index.verifies | 150 |
| abstract_inverted_index.behaviors | 162 |
| abstract_inverted_index.clarified | 79 |
| abstract_inverted_index.concepts. | 145 |
| abstract_inverted_index.estimated | 113 |
| abstract_inverted_index.function. | 117 |
| abstract_inverted_index.numerical | 119, 147 |
| abstract_inverted_index.parameter | 172 |
| abstract_inverted_index.providing | 157 |
| abstract_inverted_index.stability | 85 |
| abstract_inverted_index.conditions | 95 |
| abstract_inverted_index.controlled | 165 |
| abstract_inverted_index.estimated, | 72 |
| abstract_inverted_index.estimation | 183 |
| abstract_inverted_index.following: | 36 |
| abstract_inverted_index.introduced | 134 |
| abstract_inverted_index.mismatched | 14, 42, 169 |
| abstract_inverted_index.parameters | 43 |
| abstract_inverted_index.projective | 22 |
| abstract_inverted_index.simulation | 148 |
| abstract_inverted_index.sufficient | 94 |
| abstract_inverted_index.conditions, | 173 |
| abstract_inverted_index.considered, | 50 |
| abstract_inverted_index.controller. | 127 |
| abstract_inverted_index.controllers | 57, 60 |
| abstract_inverted_index.convergence | 77 |
| abstract_inverted_index.parameters. | 15 |
| abstract_inverted_index.significant | 89 |
| abstract_inverted_index.simulations | 120 |
| abstract_inverted_index.superiority | 124 |
| abstract_inverted_index.synchronize | 64 |
| abstract_inverted_index.theoretical | 155, 182 |
| abstract_inverted_index.Quantitative | 118 |
| abstract_inverted_index.contribution | 29 |
| abstract_inverted_index.demonstrated | 122 |
| abstract_inverted_index.demonstrates | 177 |
| abstract_inverted_index.description. | 80 |
| abstract_inverted_index.differential | 91 |
| abstract_inverted_index.furthermore, | 106 |
| abstract_inverted_index.investigates | 2 |
| abstract_inverted_index.effectiveness | 152 |
| abstract_inverted_index.incorporating | 141 |
| abstract_inverted_index.inequalities, | 92 |
| abstract_inverted_index.Mittag-Leffler | 116 |
| abstract_inverted_index.synchronization | 4, 18, 23, 69, 110, 144, 161, 185 |
| abstract_inverted_index.fractional-order | 9, 90 |
| abstract_inverted_index.quasi-Mittag-Leffler | 21 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.98570613 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |