4.6 Article

Multiple Hypothesis Testing-Based Cepstrum Thresholding for Nonparametric Spectral Estimation

期刊

IEEE SIGNAL PROCESSING LETTERS
卷 29, 期 -, 页码 2367-2371

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2022.3222949

关键词

Nonparametric spectral estimation; cepstral coefficients; FDR; FER; periodogram; multiple hypothesis testing

资金

  1. Swedish Research Council [2017-04610, 2016-06079, 2021-05022]
  2. Swedish Research Council [2021-05022] Funding Source: Swedish Research Council

向作者/读者索取更多资源

In this study, the problem of smoothed nonparametric spectral estimation via cepstrum thresholding is revisited. The cepstrum thresholding problem is formulated as a multiple hypothesis testing problem, and the false discovery rate (FDR) and familywise error rate (FER) procedures are used to threshold the cepstral coefficients. The FDR and FER approaches are compared with a previously proposed individual hypothesis testing approach, and it is shown that cepstrum thresholding based on FDR and FER can yield spectral estimates with lower mean square error (MSE).
In this letter we revisit the problem of smoothed nonparametric spectral estimation via cepstrum thresholding. We formulate the problem of cepstrum thresholding as a multiple hypothesis testing problem and use the false discovery rate (FDR) and familywise error rate (FER) procedures to threshold the cepstral coefficients. We compare the FDR and FER approaches with a previously proposed individual hypothesis testing approach and show that the cepstrum thresholding based on FDR and FER can yield spectral estimates with lower mean square error (MSE).

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