Name
Abstract | ||
|---|---|---|
We propose a novel adaptive kernel-based regression method for complex-valued signals: the generalized complex-valued kernel least-mean-square (gCKLMS). We borrow from the new results on widely linear reproducing kernel Hilbert space (WL-RKHS) for nonlinear regression and complex-valued signals, recently proposed by the authors. This paper shows that in the adaptive version of the kernel regressio... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TSP.2019.2937289 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
Kernel,Signal processing algorithms,Hilbert space,Proposals,Convergence,Signal processing,Adaptation models | Kernel (linear algebra),Convergence (routing),Hilbert space,Signal processing,Regression,Algorithm,Nonlinear regression,Kernel regression,Mathematics,Reproducing kernel Hilbert space | Journal |
Volume | Issue | ISSN |
67 | 20 | 1053-587X |
Citations | PageRank | References |
1 | 0.36 | 18 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rafael Boloix-Tortosa | 1 | 42 | 7.20 |
| Juan José Murillo-Fuentes | 2 | 182 | 23.93 |
| Sotirios A. Tsaftaris | 3 | 361 | 43.26 |