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| Titel |
A Stochastic Iterative Amplitude Adjusted Fourier Transform algorithm with improved accuracy |
| VerfasserIn |
V. Venema, F. Ament, C. Simmer |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 13, no. 3 ; Nr. 13, no. 3 (2006-07-26), S.321-328 |
| Datensatznummer |
250011776
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| Publikation (Nr.) |
 copernicus.org/npg-13-321-2006.pdf |
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| Zusammenfassung |
| A stochastic version of the Iterative Amplitude Adjusted Fourier Transform
(IAAFT) algorithm is presented. This algorithm is able to generate so-called
surrogate time series, which have the amplitude distribution and the power
spectrum of measured time series or fields. The key difference between the
new algorithm and the original IAAFT method is the treatment of the
amplitude adjustment: it is not performed for all values in each iterative
step, but only for a fraction of the values. This new algorithm achieves a
better accuracy, i.e. the power spectra of the measurement and its surrogate
are more similar. We demonstrate the improvement by applying the IAAFT
algorithm and the new one to 13 different test signals ranging from rain
time series and 3-dimensional clouds to fractal time series and theoretical
input. The improved accuracy can be important for generating high-quality
geophysical time series and fields. The traditional application of the IAAFT
algorithm is statistical nonlinearity testing. Reassuringly, we found that
in most cases the accuracy of the original IAAFT algorithm is sufficient for
this application. |
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