Name
Abstract | ||
|---|---|---|
In this paper we investigate the conditions that complex kernels must satisfy for proper complex-valued signals. We study the structure that complex kernels for proper complex-valued signals must have. Also, we demonstrate that complex kernels that have been previously proposed and used in adaptive filtering of complex-valued signals assume that those signals arc proper, i.e, they are not correlated with their complex conjugate. We provide an example of how a complex-valued kernel suitable for a particular model is designed, with a procedure that could help in other designs. The experiments included show the good behavior of the proposed kernel in the task of nonlinear channel equalization. |
Year | Venue | Keywords |
|---|---|---|
2015 | European Signal Processing Conference | Gaussian processes,regression,proper complex processes,kernel methods |
Field | DocType | ISSN |
Kernel (linear algebra),Mathematical optimization,Kernel smoother,Kernel embedding of distributions,Algorithm,Kernel principal component analysis,Adaptive filter,Kernel (image processing),Variable kernel density estimation,Mathematics,Complex conjugate | Conference | 2076-1465 |
Citations | PageRank | References |
2 | 0.39 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rafael Boloix-Tortosa | 1 | 42 | 7.20 |
| F. Javier Payan-Somet | 2 | 9 | 1.94 |
| Eva Arias-de-Reyna | 3 | 5 | 1.89 |
| Juan José Murillo-Fuentes | 4 | 182 | 23.93 |