Name
Abstract | ||
|---|---|---|
Kernel density estimation (KDE) is widely-used for non-parametric estimation of an underlying density from data. The performance of KDE is mainly dependent on the bandwidth parameter of the kernel. This study presents an alternative method of estimating the bandwidth by incorporating sparsity priors in the Fourier transform domain. By using cross-validation (CV) together with an l1 constraint, the... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1049/iet-spr.2015.0076 | IET Signal Processing |
Keywords | Field | DocType |
bandwidth allocation,compressed sensing,Fourier transforms,minimisation,parameter estimation | Kernel (linear algebra),Mathematical optimization,Multivariate kernel density estimation,Fourier transform,Bandwidth (signal processing),Variable kernel density estimation,Mathematics,Free parameter,Kernel (statistics),Kernel density estimation | Journal |
Volume | Issue | ISSN |
10 | 3 | 1751-9675 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Suhre | 1 | 3 | 1.44 |
| Orhan Arikan | 2 | 180 | 39.45 |
| Cem Emre Akbas | 3 | 8 | 3.73 |