Abstract：
:We present a novel method to iteratively calculate discrete Fourier transforms for discrete time signals with sample time intervals that may be widely nonuniform. The proposed recursive Fourier transform (RFT) does not require interpolation of the samples to uniform time intervals, and each iterative transform update of N frequencies has computational order N. Because of the inherent non-uniformity in the time between successive heart beats, an application particularly well suited for this transform is power spectral density (PSD) estimation for heart rate variability. We compare RFT based spectrum estimation with Lomb-Scargle Transform (LST) based estimation. PSD estimation based on the LST also does not require uniform time samples, but the LST has a computational order greater than Nlog(N). We conducted an assessment study involving the analysis of quasi-stationary signals with various levels of randomly missing heart beats. Our results indicate that the RFT leads to comparable estimation performance to the LST with significantly less computational overhead and complexity for applications requiring iterative spectrum estimations.
journal_name
Med Biol Eng Computjournal_title
Medical & biological engineering & computingauthors
Holland A,Aboy Mdoi
10.1007/s11517-009-0461-0subject
Has Abstractpub_date
2009-07-01 00:00:00pages
697-707issue
7eissn
0140-0118issn
1741-0444journal_volume
47pub_type
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journal_title：Medical & biological engineering & computing
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journal_title：Medical & biological engineering & computing
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journal_title：Medical & biological engineering & computing
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journal_title：Medical & biological engineering & computing
pub_type： 杂志文章,评审
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