| Full text | |
| Author(s): |
Claser, Raffaello
;
Nascimento, Vitor H.
;
Zakharov, Yuriy V.
;
IEEE
Total Authors: 4
|
| Document type: | Journal article |
| Source: | 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO); v. N/A, p. 5-pg., 2016-01-01. |
| Abstract | |
Adaptive filters for Volterra system identification must deal with two difficulties: large filter length M (resulting in high computational complexity and low convergence rate) and high correlation in the input sequence. The second problem is minimized by using the recursive least-squares algorithm (RLS), however, its large computation complexity (O(M-2)) might be prohibitive in some applications. We propose here a low-complexity RLS algorithm, based on the dichotomous coordinate descent algorithm (DCD), showing that in some situations the computational complexity is reduced to O(M). The new algorithm is compared to the standard RLS, normalized least-mean squares (NLMS) and affine projections (AP) algorithms. (AU) | |
| FAPESP's process: | 14/04256-2 - Low-cost algorithms for parameter estimation |
| Grantee: | Vitor Heloiz Nascimento |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 14/50765-6 - Knowledge-aided signal processing: theory, algorithms, implementation and applications |
| Grantee: | Vitor Heloiz Nascimento |
| Support Opportunities: | Regular Research Grants |