Exponentially anti‐synchronization control of fuzzy quaternion‐valued memristive neural networks: Matrix measure strategies and Frobenius norm methods.
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| Title: | Exponentially anti‐synchronization control of fuzzy quaternion‐valued memristive neural networks: Matrix measure strategies and Frobenius norm methods. |
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| Authors: | Si, Linli1 (AUTHOR), Li, Ruoxia1 (AUTHOR) ruoxiali1227@163.com |
| Source: | Asian Journal of Control. Mar2026, Vol. 28 Issue 2, p782-791. 10p. |
| Subjects: | Exponential stability, Artificial neural networks, Mathematical analysis, Dynamical systems, Synchronization |
| Abstract: | This study proposes a non‐decomposition method to examine the anti‐synchronization control of quaternion‐valued memristive neural networks with fuzzy terms. Using nonlinear scalarization method, the entire analysis does not use reduced order conversion, nor does it involve the separation of real and imaginary parts, but directly focuses on the original system, which preserved the integrity of the quaternion‐valued system. Furthermore, by means of the definition of x,x∈ℚ$$ \sqrt{x},x\in \mathrm{\mathbb{Q}} $$ , the quaternion‐valued memristive system is translated into a robust system with uncertain terms, which advanced some existing conclusions. Subsequently, sufficient conditions are derived to ensure the error system is exponential stable. Finally, examples are presented to demonstrate the proposed results. [ABSTRACT FROM AUTHOR] |
| Copyright of Asian Journal of Control is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 192204756 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Exponentially anti‐synchronization control of fuzzy quaternion‐valued memristive neural networks: Matrix measure strategies and Frobenius norm methods. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Si%2C+Linli%22">Si, Linli</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Ruoxia%22">Li, Ruoxia</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ruoxiali1227@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Asian+Journal+of+Control%22">Asian Journal of Control</searchLink>. Mar2026, Vol. 28 Issue 2, p782-791. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Exponential+stability%22">Exponential stability</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+analysis%22">Mathematical analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamical+systems%22">Dynamical systems</searchLink><br /><searchLink fieldCode="DE" term="%22Synchronization%22">Synchronization</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study proposes a non‐decomposition method to examine the anti‐synchronization control of quaternion‐valued memristive neural networks with fuzzy terms. Using nonlinear scalarization method, the entire analysis does not use reduced order conversion, nor does it involve the separation of real and imaginary parts, but directly focuses on the original system, which preserved the integrity of the quaternion‐valued system. Furthermore, by means of the definition of x,x∈ℚ$$ \sqrt{x},x\in \mathrm{\mathbb{Q}} $$ , the quaternion‐valued memristive system is translated into a robust system with uncertain terms, which advanced some existing conclusions. Subsequently, sufficient conditions are derived to ensure the error system is exponential stable. Finally, examples are presented to demonstrate the proposed results. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Asian Journal of Control is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/asjc.3689 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 782 Subjects: – SubjectFull: Exponential stability Type: general – SubjectFull: Artificial neural networks Type: general – SubjectFull: Mathematical analysis Type: general – SubjectFull: Dynamical systems Type: general – SubjectFull: Synchronization Type: general Titles: – TitleFull: Exponentially anti‐synchronization control of fuzzy quaternion‐valued memristive neural networks: Matrix measure strategies and Frobenius norm methods. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Si, Linli – PersonEntity: Name: NameFull: Li, Ruoxia IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 15618625 Numbering: – Type: volume Value: 28 – Type: issue Value: 2 Titles: – TitleFull: Asian Journal of Control Type: main |
| ResultId | 1 |
