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    A Statistical Study of Generalized Cell Mapping

    Source: Journal of Applied Mechanics:;1988:;volume( 055 ):;issue: 003::page 694
    Author:
    Jian-Qiao Sun
    ,
    C. S. Hsu
    DOI: 10.1115/1.3125851
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this paper a statistical error analysis of the generalized cell mapping method for both deterministic and stochastic dynamical systems is examined, based upon the statistical analogy of the generalized cell mapping method to the density estimation. The convergence of the mean square error of the one step transition probability matrix of generalized cell mapping for deterministic and stochastic systems is studied. For stochastic systems, a well-known trade-off feature of the density estimation exists in the mean square error of the one step transition probability matrix, which leads to an optimal design of generalized cell mapping for stochastic systems. The conclusions of the study are illustrated with some examples.
    keyword(s): Density , Design , Dynamic systems , Error analysis , Errors , Probability AND Stochastic systems ,
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      A Statistical Study of Generalized Cell Mapping

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    contributor authorJian-Qiao Sun
    contributor authorC. S. Hsu
    date accessioned2017-05-08T23:26:32Z
    date available2017-05-08T23:26:32Z
    date copyrightSeptember, 1988
    date issued1988
    identifier issn0021-8936
    identifier otherJAMCAV-26297#694_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/103506
    description abstractIn this paper a statistical error analysis of the generalized cell mapping method for both deterministic and stochastic dynamical systems is examined, based upon the statistical analogy of the generalized cell mapping method to the density estimation. The convergence of the mean square error of the one step transition probability matrix of generalized cell mapping for deterministic and stochastic systems is studied. For stochastic systems, a well-known trade-off feature of the density estimation exists in the mean square error of the one step transition probability matrix, which leads to an optimal design of generalized cell mapping for stochastic systems. The conclusions of the study are illustrated with some examples.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Statistical Study of Generalized Cell Mapping
    typeJournal Paper
    journal volume55
    journal issue3
    journal titleJournal of Applied Mechanics
    identifier doi10.1115/1.3125851
    journal fristpage694
    journal lastpage701
    identifier eissn1528-9036
    keywordsDensity
    keywordsDesign
    keywordsDynamic systems
    keywordsError analysis
    keywordsErrors
    keywordsProbability AND Stochastic systems
    treeJournal of Applied Mechanics:;1988:;volume( 055 ):;issue: 003
    contenttypeFulltext
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