TY - GEN
T1 - A variable step size strategy for sparse system identification
AU - Bin Saeed, Muhammad O.
AU - Zerguine, Azzedine
PY - 2013
Y1 - 2013
N2 - This work proposes a novel two-strategy approach to improve the performance of a recently-proposed (RZA-LMS) algorithm for sparse environments. The first and key strategy uses a novel l1-norm-based variable step-size scheme to improve the performance of both the conventional and the RZA-LMS algorithms. The second strategy applies to the normalization process to remove the constraint on the step size imposed by RZA-LMS algorithm by widening the range of choice of the step size. The simulation results clearly show the superiority of our proposed schemes in both sparse and non-sparse environments.
AB - This work proposes a novel two-strategy approach to improve the performance of a recently-proposed (RZA-LMS) algorithm for sparse environments. The first and key strategy uses a novel l1-norm-based variable step-size scheme to improve the performance of both the conventional and the RZA-LMS algorithms. The second strategy applies to the normalization process to remove the constraint on the step size imposed by RZA-LMS algorithm by widening the range of choice of the step size. The simulation results clearly show the superiority of our proposed schemes in both sparse and non-sparse environments.
UR - http://www.scopus.com/inward/record.url?scp=84883091945&partnerID=8YFLogxK
U2 - 10.1109/SSD.2013.6564039
DO - 10.1109/SSD.2013.6564039
M3 - Conference contribution
AN - SCOPUS:84883091945
SN - 9781467364584
T3 - 2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013
BT - 2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013
ER -