| Full text | |
| Author(s): |
Yazdanpanah, Hamed
;
Carini, Alberto
;
Lima, Markus V. S.
;
IEEE
Total Authors: 4
|
| Document type: | Journal article |
| Source: | 2019 27TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO); v. N/A, p. 5-pg., 2019-01-01. |
| Abstract | |
The paper addresses adaptive algorithms for Volterra filter identification capable of exploiting the sparsity of nonlinear systems. While the l(1)-norm of the coefficient vector is often employed to promote sparsity, it has been shown in the literature that superior results can be achieved using an approximation of the l(0)-norm. Thus, in this paper, the Geman-McClure function is adopted to approximate the l(0)-norm and to derive l(0)-norm adaptive Volterra filters. It is shown through experimental results, also involving a real-world system, that the proposed adaptive filters can obtain improved performance in comparison with classical approaches and l(1)-norm solutions. (AU) | |
| FAPESP's process: | 19/06280-1 - Integration, transformation, dataset augmentation and quality control for intermediate representation |
| Grantee: | Hamed Yazdanpanah |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 15/22308-2 - Intermediate representations in Computational Science for knowledge discovery |
| Grantee: | Roberto Marcondes Cesar Junior |
| Support Opportunities: | Research Projects - Thematic Grants |