TY  - JOUR
JF  - Signal Processing
PB  - Elsevier
IS  - 4
SN  - 0165-1684
EP  - 911
ID  - eprints1529
N2  - Sparse FIR filters have lower implementation complexity than full filters, while keeping a good performance level. This paper describes a new method for designing 1D and 2D sparse filters in the minimax sense using a mixture of reweighted l1 minimization and greedy iterations. The combination proves to be quite efficient; after the reweighted l1 minimization stage introduces zero coefficients in bulk, a small number of greedy iterations serve to eliminate a few extra coefficients. Experimental results and a comparison with the latest methods show that the proposed method performs very well both in the running speed and in the quality of the solutions obtained.
Y1  - 2012///
UR  - http://dx.doi.org/10.1016/j.sigpro.2011.09.031
A1  - Rusu, Cristian
A1  - Dumitrescu, Bogdan
VL  - 92
KW  - Sparse filters; Reweighted l1 minimization; Greedy algorithms
AV  - public
SP  - 905
TI  - Iterative reweighted l1 design of sparse FIR filters
ER  -