Stability Analysis of Recurrent-Neural-Based Controllers Using Dissipativity Domain

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dc.contributor.authorJafari, Rezaen
dc.date.accessioned2023-07-28T14:50:20Zen
dc.date.available2023-07-28T14:50:20Zen
dc.date.issued2023-07-10en
dc.date.updated2023-07-28T12:21:41Zen
dc.description.abstractThis paper proposes a method for the stability analysis of dynamic neural networks. The stability analysis of dynamic neural networks is a challenging task due to internal feedback connections. In this research work, we propose an algorithm based on the Reduction of Dissipativity Domain (RODD) algorithm. The RODD algorithm is a numerical technique for the detection of the stability of nonlinear dynamic systems. The method works by using an approximation of the reachable set. This paper proposes linear and quadratic approximations of reachable sets. RODD-LB uses a linear approximation, RODD-EB uses a quadratic approximation, and the RODD-Hybrid algorithm uses a combination of the linear and quadratic approximations. The accuracy and convergence of these algorithms were derived through numerical dynamic systems.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationJafari, R. Stability Analysis of Recurrent-Neural-Based Controllers Using Dissipativity Domain. Mathematics 2023, 11, 3050.en
dc.identifier.doihttps://doi.org/10.3390/math11143050en
dc.identifier.urihttp://hdl.handle.net/10919/115939en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectrecurrent neural networken
dc.subjectstability analysisen
dc.subjectdissipativity domainen
dc.subjectreachable seten
dc.subjectlinear and quadratic approximation of reachable seten
dc.titleStability Analysis of Recurrent-Neural-Based Controllers Using Dissipativity Domainen
dc.title.serialMathematicsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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