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    Using a Lanczos Eigensolver in the Computation of Empirical Orthogonal Functions

    Source: Monthly Weather Review:;2001:;volume( 129 ):;issue: 005::page 1243
    Author:
    Toumazou, Vincent
    ,
    Cretaux, Jean-Francois
    DOI: 10.1175/1520-0493(2001)129<1243:UALEIT>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: In the framework of physical field studies, EOF analysis allows the scientist to determine the modes that govern the variability of a phenomenon. The analysis requires the resolution of a linear algebra problem. This paper focuses on this part of the EOF analysis, the computation of some singular values, and the associated vectors of the data matrix D. After recalling some fundamentals of this type of problem, the authors compare the usually employed singular value decomposition strategy with a Lanczos eigensolver technique. The latter consists of computing some eigenvalues of a small symmetric matrix. The authors demonstrate its mathematical and numerical stability and discuss its main features. A comparison of the two strategies shows the advantages of the Lanczos technique. Finally, the approach is illustrated with an example based on the study of oceanographic datasets.
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      Using a Lanczos Eigensolver in the Computation of Empirical Orthogonal Functions

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4204766
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    contributor authorToumazou, Vincent
    contributor authorCretaux, Jean-Francois
    date accessioned2017-06-09T16:13:41Z
    date available2017-06-09T16:13:41Z
    date copyright2001/05/01
    date issued2001
    identifier issn0027-0644
    identifier otherams-63731.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4204766
    description abstractIn the framework of physical field studies, EOF analysis allows the scientist to determine the modes that govern the variability of a phenomenon. The analysis requires the resolution of a linear algebra problem. This paper focuses on this part of the EOF analysis, the computation of some singular values, and the associated vectors of the data matrix D. After recalling some fundamentals of this type of problem, the authors compare the usually employed singular value decomposition strategy with a Lanczos eigensolver technique. The latter consists of computing some eigenvalues of a small symmetric matrix. The authors demonstrate its mathematical and numerical stability and discuss its main features. A comparison of the two strategies shows the advantages of the Lanczos technique. Finally, the approach is illustrated with an example based on the study of oceanographic datasets.
    publisherAmerican Meteorological Society
    titleUsing a Lanczos Eigensolver in the Computation of Empirical Orthogonal Functions
    typeJournal Paper
    journal volume129
    journal issue5
    journal titleMonthly Weather Review
    identifier doi10.1175/1520-0493(2001)129<1243:UALEIT>2.0.CO;2
    journal fristpage1243
    journal lastpage1250
    treeMonthly Weather Review:;2001:;volume( 129 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian