Abstract
The fast orthogonal search (FOS) algorithm has been shown to accurately model various types of time series by implicitly creating a specialized orthogonal basis set to fit the desired time series. When the data contain periodic components, FOS can find frequencies with a resolution greater than the discrete Fourier transform (DFT) algorithm. Frequencies with less than one period in the record length, called subharmonic frequencies, and frequencies between the bins of a DFT, can be resolved. This paper considers the resolution of subharmonic frequencies using the FOS algorithm. A new criterion for determining the number of non-noise terms in the model is introduced. This new criterion does not assume the first model term fitted is a dc component as did the previous stopping criterion. An iterative FOS algorithm called FOS first-term reselection (FOS-FTR), is introduced. FOS-FTR reduces the mean-square error of the sinusoidal model and selects the subharmonic frequencies more accurately than does the unmodified FOS algorithm. © 2003 Biomedical Engineering Society.
PAC2003: 8780Tq, 0270Hm
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McGaughey, D.R., Korenberg, M.J., Adeney, K.M. et al. Using the Fast Orthogonal Search with First Term Reselection to Find Subharmonic Terms in Spectral Analysis. Annals of Biomedical Engineering 31, 741–751 (2003). https://doi.org/10.1114/1.1574024
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DOI: https://doi.org/10.1114/1.1574024