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    A. Boudou and S. Viguier-Pla (2020)
    Principal Components Analysis of a Cyclostationary Random Function.

    Classification
    60G57, 60G10, 60B15, 60H05
    Keywords
    Cyclostationary random function, Orthogonal projector, Random measure, Spectral measure, Stationary process, Unitary operator
    Abstract : Principal Components Analysis is a well-known method for reduction of dimension in Data Analysis. Considering a cyclostationary random function, we use appropriate transformations, based on spectral properties, in order to get a stationary random function, and then to process to a principal components analysis in the frequency domain. Then, a cyclostationary function is reconstituted as a summary of the initial cyclostationary function. Applications on simulated data illustrate the method.