Name
Abstract | ||
|---|---|---|
In this paper, we introduce a time-frequency spectral estimator for smooth spectra, allowing for irregularly sampled measurements. A non-parametric representation of the time dependent (TD) covariance matrix is formed by assuming that the spectrum is piecewise linear. Using this representation, the time-frequency spectrum is then estimated by solving a convex covariance fitting problem, which also, as a byproduct, provides an enhanced estimation of the TD covariance matrix. Numerical examples using simulated non-stationary processes show the preferable performance of the proposed method as compared to the classical Wigner-Ville distribution and a smoothed spectrogram. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICASSP.2014.6853702 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
covariance matrices,curve fitting,piecewise linear techniques,signal representation,smoothing methods,spectral analysis,time-frequency analysis,TD covariance matrix,Wigner-Ville distribution,convex covariance fitting problem,irregularly sampled measurements,non-parametric representation,non-stationary processes,piecewise linear,smooth spectra,smooth time-frequency estimation,smoothed spectrogram,time dependent covariance matrix,time-frequency spectral estimator,time-frequency spectrum | Mathematical optimization,Covariance function,Estimation of covariance matrices,Rational quadratic covariance function,Covariance intersection,CMA-ES,Covariance matrix,Matérn covariance function,Mathematics,Covariance | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Johan Brynolfsson | 1 | 10 | 5.36 |
| Johan Sward | 2 | 37 | 11.84 |
| Andreas Jakobsson | 3 | 409 | 43.32 |
| Maria Hansson-Sandsten | 4 | 93 | 17.25 |