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ESTIMATION OF MULTIPLE SINUSOIDAL FREQUENCIES USING TRUNCATED LEAST-SQUARES METHODS

dc.citation.epage994en_US
dc.citation.issue2en_US
dc.citation.spage990en_US
dc.citation.volume41en_US
dc.citation.woscount6
dc.contributor.authorHSIEH, SFen_US
dc.contributor.authorLIU, KJRen_US
dc.contributor.authorYAO, Ken_US
dc.contributor.department電信工程研究所zh_TW
dc.contributor.departmentInstitute of Communications Engineeringen_US
dc.date.accessioned2014-12-08T15:04:38Z
dc.date.available2014-12-08T15:04:38Z
dc.date.issued1993-02-01en_US
dc.description.abstractVarious SVD-based methods have been shown effective for resolving closely spaced frequencies. However, the massive computations required by SVD makes it unsuitable for real-time applications. To reduce the computational complexity, three truncated QR methods are proposed: 1) truncated QR without column pivoting (TQR); 2) truncated QR with reordered columns (TQRR); and 3) truncated QR with column pivoting (TQRP). It is demonstrated that many of the benefits of the SVD-based methods are achievable under the truncated QR methods with much lower computational cost. Based on the forward-backward linear prediction model, computer simulations and comparisons are provided for different truncation methods under various SNR's. Comparisons of asymptotic performance with large data samples are also given.en_US
dc.identifier.doi10.1109/78.193242en_US
dc.identifier.issn1053-587Xen_US
dc.identifier.journalIEEE TRANSACTIONS ON SIGNAL PROCESSINGen_US
dc.identifier.urihttp://dx.doi.org/10.1109/78.193242en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/3125
dc.identifier.wosnumberWOS:A1993KL82300048
dc.language.isoen_USen_US
dc.titleESTIMATION OF MULTIPLE SINUSOIDAL FREQUENCIES USING TRUNCATED LEAST-SQUARES METHODSen_US
dc.typeLetteren_US

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