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Automatic Detection, Estimation, and Validation of Harmonic Components in Measured Power Spectra: All-in-One Approach
The detection of periodic components buried in noise is a general problem in various engineering fields. The amplitudes in the frequency domain of a disturbed signal follow Rice distribution, which is fully described by two parameters. Most methods are restricted to automatically detecting the harmo...
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Published in: | IEEE transactions on instrumentation and measurement 2011-03, Vol.60 (3), p.1061-1069 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The detection of periodic components buried in noise is a general problem in various engineering fields. The amplitudes in the frequency domain of a disturbed signal follow Rice distribution, which is fully described by two parameters. Most methods are restricted to automatically detecting the harmonic components. In this paper, we extend the methodology to detect significant harmonics in measured spectra such that, aside from detection, the magnitude of the harmonic component is also estimated, together with the probability that the harmonic component was incorrectly detected. |
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ISSN: | 0018-9456 1557-9662 |
DOI: | 10.1109/TIM.2010.2062710 |