Model transform and local parameters. Application to instantaneous attractors.
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| Title: | Model transform and local parameters. Application to instantaneous attractors. |
|---|---|
| Authors: | Galadí, J.A.1,2 (AUTHOR) jgaladi@us.es, Soler-Toscano, F.3 (AUTHOR), Langa, J.A.4 (AUTHOR) |
| Source: | Chaos, Solitons & Fractals. Jun2022, Vol. 159, pN.PAG-N.PAG. 1p. |
| Subjects: | Dynamical systems, Systems theory |
| Abstract: | The model transform fits exactly the parameters of a suitable model to empirical or simulated data in each point in time and/or space. We describe several examples of concrete model transforms and their applications. The model transform allows simple theoretical models to be applied to complex empirical systems in each short interval of time or/and in each local neighborhood. The model can be chosen to identify, for instance, the temporal evolution of the attractor landscape for empirical systems which depict a complex dynamics over time. • A new tool, the Model Transform , applies simple models to complex systems. • The aim is not to model but to find new measurements to characterize systems. • As an application, we approximate a non-stationary attractor landscape. • Any model in any discipline leads to new applications of the Model Transform. [ABSTRACT FROM AUTHOR] |
| Copyright of Chaos, Solitons & Fractals is the property of Pergamon Press - An Imprint of Elsevier Science 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 |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 157075939 AccessLevel: 6 PubType: Periodical PubTypeId: serialPeriodical PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Model transform and local parameters. Application to instantaneous attractors. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Galadí%2C+J%2EA%2E%22">Galadí, J.A.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> jgaladi@us.es</i><br /><searchLink fieldCode="AR" term="%22Soler-Toscano%2C+F%2E%22">Soler-Toscano, F.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Langa%2C+J%2EA%2E%22">Langa, J.A.</searchLink><relatesTo>4</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Chaos%2C+Solitons+%26+Fractals%22">Chaos, Solitons & Fractals</searchLink>. Jun2022, Vol. 159, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Dynamical+systems%22">Dynamical systems</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+theory%22">Systems theory</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The model transform fits exactly the parameters of a suitable model to empirical or simulated data in each point in time and/or space. We describe several examples of concrete model transforms and their applications. The model transform allows simple theoretical models to be applied to complex empirical systems in each short interval of time or/and in each local neighborhood. The model can be chosen to identify, for instance, the temporal evolution of the attractor landscape for empirical systems which depict a complex dynamics over time. • A new tool, the Model Transform , applies simple models to complex systems. • The aim is not to model but to find new measurements to characterize systems. • As an application, we approximate a non-stationary attractor landscape. • Any model in any discipline leads to new applications of the Model Transform. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Chaos, Solitons & Fractals is the property of Pergamon Press - An Imprint of Elsevier Science 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: 10.1016/j.chaos.2022.112094 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Dynamical systems Type: general – SubjectFull: Systems theory Type: general Titles: – TitleFull: Model transform and local parameters. Application to instantaneous attractors. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Galadí, J.A. – PersonEntity: Name: NameFull: Soler-Toscano, F. – PersonEntity: Name: NameFull: Langa, J.A. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 09600779 Numbering: – Type: volume Value: 159 Titles: – TitleFull: Chaos, Solitons & Fractals Type: main |
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