Fast algorithm for spectral analysis of unevenly sampled data

Details Fast algorithm for spectral analysis of unevenly sampled data Fast algorithm for spectral analysis of unevenly sampled data

Mar 1989

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1989apj...338..277p&link_type=abstract

Astrophysical Journal, Part 1 (ISSN 0004- 637X), vol. 338, March 1, 1989, p. 277-280.

Statistics

Computation

224

Algorithms, Data Sampling, Fast Fourier Transformations, Spectrum Analysis, Computer Programs, Fortran

Scientific paper

The Lomb-Scargle method performs spectral analysis on unevenly sampled data and is known to be a powerful way to find, and test the significance of, weak periodic signals. The method has previously been thought to be 'slow', requiring of order 10(2)N(2) operations to analyze N data points. We show that Fast Fourier Transforms (FFTs) can be used in a novel way to make the computation of order 10(2)N log N. Despite its use of the FFT, the algorithm is in no way equivalent to conventional FFT periodogram analysis.

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