Alves Martins, Wallace[University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Lima, Markus[Federal University of Rio de Janeiro (UFRJ)]
Diniz, Paulo[Federal University of Rio de Janeiro (UFRJ)]
May-2019
Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
4858-4862
Yes
No
International
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-2019)
12-17 May 2019
[en] Set-membership affine projection (SM-AP) adaptive filters have been increasingly employed in the context of online data-selective learning. A key aspect for their good performance in terms of both convergence speed and steady-state mean-squared error is the choice of the so-called constraint vector. Optimal constraint vectors were recently proposed relying on convex optimization tools, which might some- times lead to prohibitive computational burden. This paper proposes a convex combination of simpler constraint vectors whose performance approaches the optimal solution closely, utilizing much fewer computations. Some illustrative examples confirm that the sub-optimal solution follows the accomplishments of the optimal one.