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The spectral kurtosis: a useful tool for characterising non-stationary signals
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- R.F. Dwyer, A technique for improving detection and estimation of signals contaminated by under ice noise, Journal of the Acoustical Society of America 74 (1) (1983) 124–130. · doi:10.1121/1.389729
- Dwyer, 1984, Use of the kurtosis statistic in the frequency domain as an aid in detecting random signals, IEEE Journal of Oceanic Engineering, OE-9, 85, 10.1109/JOE.1984.1145602 · DOI
- S.-F. Lei, et al., The application of frequency and time domain kurtosis to the assessment of hazardous noise exposures, Journal of the Acoustical Society of America 96 (3) (1994) 1435–1444. · doi:10.1121/1.410287
- Otonnello, 1994, Modified frequency domain kurtosis for signal processing, Electronics Letters, 30, 1117, 10.1049/el:19940777 · doi:10.1049/el:19940777
- S. Pagnan, et al., Filtering of randomly occurring signals by kurtosis in the frequency domain, Proceedings of the 12th International Conference on Pattern Recognition, vol. 3, October 1994, pp. 131–133. · doi:10.1109/icpr.1994.577137
- V. Capdevielle, C. Servière, J.-L. Lacoume, Blind separation of wide-band sources: application to rotating machine signals, Proceedings of the Eighth European Signal Processing Conference, vol. 3, 1996, pp. 2085–2088.
- V.D. Vrabie, P. Granjon, Harmonic component characterization using spectral kurtosis, 12th European Signal Processing Conference, September 7–10, 2004, Vienna, Austria, submitted for publication.
- Zadeh, 1950, Circuit analysis of linear varying-parameter networks, Journal of Applied Physics, 21, 1171, 10.1063/1.1699560 · doi:10.1063/1.1699560
- J. Antoni, Cyclostationary modelling of rotating machine vibration signals, Mechanical Systems and Signal Processing 18 (6) (2004) 1285–1314. · DOI
- Feng, 1996, Design of Wiener filters using cumulant based MSE criterion, Signal Processing, 54, 23, 10.1016/0165-1684(96)00091-6 · DOI
- P.D. Welch, A direct digital method of power spectrum estimation, IBM Journal (1961) 141–156. · doi:10.1147/rd.52.0141
- Portnoff, 1980, Time–frequency representation of digital signals and systems based on short-time Fourier analysis, IEEE Transactions on Acoustics, Speech and Signal Processing, ASSP-28, 55, 10.1109/TASSP.1980.1163359 · DOI · Paper page
- R.A. Silverman, Locally stationary random processes, I.R.E. Transactions on Information Theory (1957) 182–187. · doi:10.1109/tit.1957.1057413
- M. Rosenblatt, Some comments on band-pass filters, Quarterly of Applied Mathematics 18 387–393. · doi:10.1090/qam/121867
- Mendel, 1991, Tutorial on higher-order statistics (spectra) in signal processing and system theory, IEEE Proceedings, 79, 278, 10.1109/5.75086 · DOI · Paper page
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Metadata
- Authors
- Antoni, J.
- Venue
- Mechanical Systems and Signal Processing
- Publisher
- Elsevier BV
- Published
- 2006-02
- Volume
- 20
- Issue
- 2
- Pages
- 282-307
- ISSN
- 0888-3270 (ISSN-L)
- OpenAlex
- W2046674752
- Cited by
- 1,441
- References
- 0
- FWCI
- 13.56
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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- Antoni, J. (2006). The spectral kurtosis: a useful tool for characterising non-stationary signals. Mechanical Systems and Signal Processing. https://doi.org/10.1016/j.ymssp.2004.09.001
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
