| Full text | |
| Author(s): |
Diniz, Paulo S. R.
;
Yazdanpanah, Named
;
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 | |
Sparse representations of model parameters have been widely studied. In the adaptive filtering literature, most studies address the cases where the sparsity is directly observed, therefore, there is a growing interest in developing strategies to exploit hidden sparsity. Recently, the feature LMS (F-LMS) algorithm was proposed to expose the sparsity of models with low- and high-frequency contents. In this paper, the F-LMS algorithm is extended to expose hidden sparsity related to models with bandpass spectrum, including the cases of narrowband and broader passband sources. Some simulation results show that the proposed approaches lead to F-LMS algorithms with fast convergence, low misadjustment after convergence, and low computational cost. (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 |