Name
Abstract | ||
|---|---|---|
Algebraic averaging is widely used in nonparametric methods of power spectral estimation. Geometric averaging has been proposed as a nonlinear nonparametric method that may result in lesser variance and bias. In this paper we proposed two nonparametric power spectral estimation methods that employ geometric averaging in conjunction with algebraic averaging. The first method gives improvements in frequency resolution and dynamic range for periodic signals. The second method presented enhances frequency resolution for closely spaced frequencies. |
Year | Venue | Keywords |
|---|---|---|
2005 | Seventh IASTED International Conference on Signal and Image Processing | periodogram,Fourier transform,spectral analyses,detection and estimation |
Field | DocType | Citations |
Applied mathematics,Maximum entropy spectral estimation,Mathematical optimization,Spectral density estimation,Algebraic number,Mathematics | Conference | 0 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gordana Velikic | 1 | 10 | 8.37 |
| Babak Razavi | 2 | 0 | 0.34 |
| Mark F. Bocko | 3 | 53 | 13.19 |
| Tolga Numanoglu | 4 | 10 | 5.61 |
| Edward L. Titlebaum | 5 | 49 | 11.59 |