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    Complex Principal Component Analysis: Theory and Examples

    Source: Journal of Climate and Applied Meteorology:;1984:;volume( 023 ):;issue: 012::page 1660
    Author:
    Horel, J. D.
    DOI: 10.1175/1520-0450(1984)023<1660:CPCATA>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: Complex principal component (CPC) analysis is shown to be a useful method for identifying traveling and standing waves in geophysical data sets. Combinations of simple progressive and standing oscillations are used to examine the properties of this technique. These examples illustrate that although CPC analysis allows for the identification of traveling waves, many of the drawbacks associated with conventional principal component analysis remain, and sometimes become worse; e.g. the interpretation of CPC solutions is more difficult since both amplitude and phase relationships must be considered. A method for linearly transforming complex principal components was devised in order to identify regional relationships within large geophysical data sets. The errors in CPC analysis resulting from limited sample sizes are discussed.
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      Complex Principal Component Analysis: Theory and Examples

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4145953
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    contributor authorHorel, J. D.
    date accessioned2017-06-09T14:00:26Z
    date available2017-06-09T14:00:26Z
    date copyright1984/12/01
    date issued1984
    identifier issn0733-3021
    identifier otherams-10797.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4145953
    description abstractComplex principal component (CPC) analysis is shown to be a useful method for identifying traveling and standing waves in geophysical data sets. Combinations of simple progressive and standing oscillations are used to examine the properties of this technique. These examples illustrate that although CPC analysis allows for the identification of traveling waves, many of the drawbacks associated with conventional principal component analysis remain, and sometimes become worse; e.g. the interpretation of CPC solutions is more difficult since both amplitude and phase relationships must be considered. A method for linearly transforming complex principal components was devised in order to identify regional relationships within large geophysical data sets. The errors in CPC analysis resulting from limited sample sizes are discussed.
    publisherAmerican Meteorological Society
    titleComplex Principal Component Analysis: Theory and Examples
    typeJournal Paper
    journal volume23
    journal issue12
    journal titleJournal of Climate and Applied Meteorology
    identifier doi10.1175/1520-0450(1984)023<1660:CPCATA>2.0.CO;2
    journal fristpage1660
    journal lastpage1673
    treeJournal of Climate and Applied Meteorology:;1984:;volume( 023 ):;issue: 012
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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