2020
DOI: 10.1007/s00773-020-00768-9
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Estimation of autocorrelation function and spectrum density of wave-induced responses using prolate spheroidal wave functions

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Cited by 10 publications
(16 citation statements)
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References 31 publications
(43 reference statements)
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“…However, in (Takami et al, 2020b), a problem in making predictions using PSWF-based ACFs was found and discussed; a 'numerical concern' related to inversion of the AC matrix, which can become non-positive definite when the PSWF-based ACF is introduced. Although the sample AC matrix, per se, should be nonnegative definite (McLeod and Jimenez, 1984), it is not necessarily the case for the PSWF-based AC matrices.…”
Section: Acfmentioning
confidence: 99%
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“…However, in (Takami et al, 2020b), a problem in making predictions using PSWF-based ACFs was found and discussed; a 'numerical concern' related to inversion of the AC matrix, which can become non-positive definite when the PSWF-based ACF is introduced. Although the sample AC matrix, per se, should be nonnegative definite (McLeod and Jimenez, 1984), it is not necessarily the case for the PSWF-based AC matrices.…”
Section: Acfmentioning
confidence: 99%
“…This largelag time error influences the prediction accuracy and smoothing of the ACF or the associated PSD is therefore necessary (Nielsen et al, 2018). Recently, the authors presented a new approach for obtaining smoothed ACF and PSD from short-time measurements (Takami et al, 2020b). In (Takami et al, 2020b), the PSWF (Slepian and Pollak, 1961) were used to taper the sample ACF for reducing the large-lag time errors.…”
mentioning
confidence: 99%
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