Fitting FFT-derived Spectra: Theory, Tool, and Application to Solar Radio Spike Decomposition
Abstract
Spectra derived from fast Fourier transform (FFT) analysis of time-domain data intrinsically contain statistical fluctuations whose distribution depends on the number of accumulated spectra contributing to a measurement. The tail of this distribution, which is essential for separation of the true signal from the statistical fluctuations, deviates noticeably from the normal distribution for a finite number of the accumulations. In this paper we develop a theory to properly account for the statistical fluctuations when fitting a model to a given accumulated spectrum. The method is implemented in software for the purpose of automatically fitting a large body of such FFT-derived spectra. We apply this tool to analyze a portion of a dense cluster of spikes recorded by our FST instrument during a record-breaking event that occurred on 06 Dec 2006. The outcome of this analysis is briefly discussed.
Keywords
Cite
@article{arxiv.1406.2280,
title = {Fitting FFT-derived Spectra: Theory, Tool, and Application to Solar Radio Spike Decomposition},
author = {Gelu M. Nita and Gregory D. Fleishman and Dale E. Gary and William Marin and Kristine Boone},
journal= {arXiv preprint arXiv:1406.2280},
year = {2015}
}
Comments
Accepted to ApJ, 57 pages, 16 figures