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The application of the cell mapping method in the characteristic diagnosis of nonlinear dynamical systems
The cell mapping method is one of the most powerful tools in the global analysis of nonlinear dynamical systems. It accurately depicts the boundaries of the domains of attractors but is not the ideal method for diagnosing the characteristics of attractors. To improve the performance of the conventio...
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Published in: | Nonlinear dynamics 2023-10, Vol.111 (19), p.18095-18112 |
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description | The cell mapping method is one of the most powerful tools in the global analysis of nonlinear dynamical systems. It accurately depicts the boundaries of the domains of attractors but is not the ideal method for diagnosing the characteristics of attractors. To improve the performance of the conventional cell mapping method, an approach telling quasiperiodicity from chaos is developed in the current research. The proposed method uses the convergence speed of a probability distribution on the attractor as the criterion. For a chaotic system, the distribution converges quickly to the invariant density in several iterations. As for a quasiperiodic system, the distribution converges extremely slowly to the invariant density. The difference can be explained by the eigenvalues of the transition matrices of different systems. The transition matrix of a chaotic system has irregular eigenvalues, and the second-largest eigenvalue is small enough, while the matrix of a quasiperiodic system has regular eigenvalues, many of which are close to the unit circle. A theoretical analysis of some simple mappings is addressed to support this explanation. Furthermore, as a supplement to the analysis, a numerical method that calculates the Lyapunov exponent from the transition matrix is also discussed. |
doi_str_mv | 10.1007/s11071-023-08777-0 |
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-30d93791e898e36f246f46b05279fc250bb87fd56e60550dfde7ba7a1169cb523</citedby><cites>FETCH-LOGICAL-c319t-30d93791e898e36f246f46b05279fc250bb87fd56e60550dfde7ba7a1169cb523</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Zhang, Zhengyuan</creatorcontrib><creatorcontrib>Dai, Liming</creatorcontrib><title>The application of the cell mapping method in the characteristic diagnosis of nonlinear dynamical systems</title><title>Nonlinear dynamics</title><addtitle>Nonlinear Dyn</addtitle><description>The cell mapping method is one of the most powerful tools in the global analysis of nonlinear dynamical systems. 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A theoretical analysis of some simple mappings is addressed to support this explanation. Furthermore, as a supplement to the analysis, a numerical method that calculates the Lyapunov exponent from the transition matrix is also discussed.</description><subject>Attractors (mathematics)</subject><subject>Automotive Engineering</subject><subject>Cell mapping method</subject><subject>Chaos theory</subject><subject>Classical Mechanics</subject><subject>Control</subject><subject>Convergence</subject><subject>Density</subject><subject>Dynamical Systems</subject><subject>Eigenvalues</subject><subject>Engineering</subject><subject>Invariants</subject><subject>Liapunov exponents</subject><subject>Mechanical Engineering</subject><subject>Nonlinear systems</subject><subject>Numerical methods</subject><subject>Original Paper</subject><subject>Vibration</subject><issn>0924-090X</issn><issn>1573-269X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kE9LAzEQxYMoWKtfwFPA8-okaTaboxT_QcFLhd5CNpu0KbtJTbaHfnujK3jzNDDv_d4wD6FbAvcEQDxkQkCQCiiroBFCVHCGZoQLVtFabs7RDCRdVCBhc4muct4DAKPQzJBf7yzWh0PvjR59DDg6PJaVsX2PhyL4sMWDHXexwz5M0k4nbUabfB69wZ3X2xCzz99oiKH3weqEu1PQQwntcT7l0Q75Gl043Wd78zvn6OP5ab18rVbvL2_Lx1VlGJFjxaCTTEhiG9lYVju6qN2iboFTIZ2hHNq2Ea7jta2Bc-hcZ0WrhSaklqbllM3R3ZR7SPHzaPOo9vGYQjmpaMObpjwuWHHRyWVSzDlZpw7JDzqdFAH1XamaKlWlUvVTqYICsQnKxRy2Nv1F_0N9ATYFeqE</recordid><startdate>20231001</startdate><enddate>20231001</enddate><creator>Zhang, Zhengyuan</creator><creator>Dai, Liming</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope></search><sort><creationdate>20231001</creationdate><title>The application of the cell mapping method in the characteristic diagnosis of nonlinear dynamical systems</title><author>Zhang, Zhengyuan ; Dai, Liming</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-30d93791e898e36f246f46b05279fc250bb87fd56e60550dfde7ba7a1169cb523</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Attractors (mathematics)</topic><topic>Automotive Engineering</topic><topic>Cell mapping method</topic><topic>Chaos theory</topic><topic>Classical Mechanics</topic><topic>Control</topic><topic>Convergence</topic><topic>Density</topic><topic>Dynamical Systems</topic><topic>Eigenvalues</topic><topic>Engineering</topic><topic>Invariants</topic><topic>Liapunov exponents</topic><topic>Mechanical Engineering</topic><topic>Nonlinear systems</topic><topic>Numerical methods</topic><topic>Original Paper</topic><topic>Vibration</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Zhengyuan</creatorcontrib><creatorcontrib>Dai, Liming</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><jtitle>Nonlinear dynamics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Zhengyuan</au><au>Dai, Liming</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The application of the cell mapping method in the characteristic diagnosis of nonlinear dynamical systems</atitle><jtitle>Nonlinear dynamics</jtitle><stitle>Nonlinear Dyn</stitle><date>2023-10-01</date><risdate>2023</risdate><volume>111</volume><issue>19</issue><spage>18095</spage><epage>18112</epage><pages>18095-18112</pages><issn>0924-090X</issn><eissn>1573-269X</eissn><abstract>The cell mapping method is one of the most powerful tools in the global analysis of nonlinear dynamical systems. It accurately depicts the boundaries of the domains of attractors but is not the ideal method for diagnosing the characteristics of attractors. To improve the performance of the conventional cell mapping method, an approach telling quasiperiodicity from chaos is developed in the current research. The proposed method uses the convergence speed of a probability distribution on the attractor as the criterion. For a chaotic system, the distribution converges quickly to the invariant density in several iterations. As for a quasiperiodic system, the distribution converges extremely slowly to the invariant density. The difference can be explained by the eigenvalues of the transition matrices of different systems. The transition matrix of a chaotic system has irregular eigenvalues, and the second-largest eigenvalue is small enough, while the matrix of a quasiperiodic system has regular eigenvalues, many of which are close to the unit circle. 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subjects | Attractors (mathematics) Automotive Engineering Cell mapping method Chaos theory Classical Mechanics Control Convergence Density Dynamical Systems Eigenvalues Engineering Invariants Liapunov exponents Mechanical Engineering Nonlinear systems Numerical methods Original Paper Vibration |
title | The application of the cell mapping method in the characteristic diagnosis of nonlinear dynamical systems |
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