Issue No. 05 - September/October (2005 vol. 7)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCSE.2005.103
Bert Rust , Siena College
Denis Donnelly , US National Institute for Standards and Technology
In Part I, we introduced the idea of windowing a time series before estimating its frequency spectrum. In addition to some fundamental elements, we examined zero padding, aliasing, the relationship to a Fourier series, and windowing. One disadvantage of windowing is that it alters or restricts the data, which, of course, has consequences for the spectral estimate. In this installment, we continue our discussion from that first installment with a more general approach to computing spectrum estimates via the FFT.
fast Fourier transform, FFT, spectral analysis, time series data
D. Donnelly and B. Rust, "The Fast Fourier Transform for Experimentalists Part III: Classical Spectral Analysis," in Computing in Science & Engineering, vol. 7, no. , pp. 74-78, 2005.