Detection Test for Periodic Signals Revisited Against Various Stochastic Models
Detection Test for Periodic Signals Revisited Against Various Stochastic Models
复制标题
针对各种随机模型重新审视周期性信号的检测测试
DOI：
10.1109/access.2019.2927445
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发表时间：
2019
期刊：
影响因子：
3.9
通讯作者：
Chang Xu
中科院分区：
文献类型：
--
作者：
Chang Xu
在寻找隐藏于红噪声中的周期性或准周期性振荡时，应考虑适当的噪声背景。假设常规一阶自回归（AR(1)）过程的零假设可能会导致误导性结论。
Appropriate noise background should be taken into account when searching for the periodic or quasi-periodic oscillation buried in red noise. Null hypothesis assuming a conventional first-order autoregressive (AR(1)) process may lead to misleading conclusions since we know from many other studies that the noise in astrophysical and geographical sources exhibit the Fourier power-law-like properties. We improve the detection of periodic signals with the multitaper spectrum and wavelet spectrum by systematically taking into account a more appropriate null hypothesis (noise background) along with the multiple testing to test against. The confident level is determined with the noise contents obtained by using the maximum likelihood estimation (MLE) technique in the time domain, along with the data error covariance constructed using the fractional differencing. Not only traditional AR(1), but also the generalized Gauss–Markov, power law, and autoregressive fractionally integrated moving average (ARFIMA) process are included as possible candidate null hypothesis. The Bayesian Information Criterion (BIC) is adopted to quantify how well the candidate noise models fit the data under consideration. Our method is demonstrated on pre-seismic electromagnetic emissions, weight-percentage calcium carbonate data, and sea surface temperature anomaly variability. The result shows that our approach has a more extensive value of the application.
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影响因子：
2.4
作者：
Fraedrich, K;Luksch, U;Blender, R
通讯作者：
Blender, R
影响因子：
--
作者：
S. Meyers
通讯作者：
S. Meyers
影响因子：
4.6
作者：
D. Dommenget;M. Latif
通讯作者：
D. Dommenget;M. Latif
影响因子：
2.4
作者：
Maraun, D.;Kurths, J.;Holschneider, M.
通讯作者：
Holschneider, M.
DOI：
--
发表时间：
2009
期刊：
--
影响因子：
--
作者：
M. Mudelsee;D. Scholz;R. Röthlisberger;D. Fleitmann;A. Mangini;E. W. Wolff
通讯作者：
M. Mudelsee;D. Scholz;R. Röthlisberger;D. Fleitmann;A. Mangini;E. W. Wolff