| Texto completo | |
| Autor(es): |
Yazdanpanah, Hamed
;
Carini, Alberto
;
Lima, Markus V. S.
;
IEEE
Número total de Autores: 4
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2019 27TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO); v. N/A, p. 5-pg., 2019-01-01. |
| Resumo | |
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) | |
| Processo FAPESP: | 19/06280-1 - Integração, transformação, aumento de dados e controle de qualidade para representações intermediárias |
| Beneficiário: | Hamed Yazdanpanah |
| Modalidade de apoio: | Bolsas no Brasil - Pós-Doutorado |
| Processo FAPESP: | 15/22308-2 - Representações intermediárias em Ciência Computacional para descoberta de conhecimento |
| Beneficiário: | Roberto Marcondes Cesar Junior |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |