.png){kind=icon}
.png){kind=icon}
Return
Affine projection sign algorithm with l1 minimization-based variable step-size
.png){kind=icon}
PRE
AI
DOI：10.1016/j.sigpro.2014.06.006.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, a new affine projection sign algorithm with a variable step-size, robust in impulsive noise environments, is proposed. For that purpose, l(1)-norm of the a posteriori error vector is minimized under a box constraint on the step-size. Since the proposed l(1)-norm minimization problem is non-differentiable convex one, an efficient numerical procedure is developed for the affine projection structure algorithm. Finally, it is demonstrated that the proposed algorithm, not requiring any a priori knowledge, yields more robust convergence in various impulsive noise environments than conventional algorithms with robustness to outliers and recent variable step-size algorithms with a priori information. (c) 2014 Elsevier B.V. All rights reserved.
Keywords:
Adaptive filter
Affine projection sign algorithm
Variable step-size
l(1)-norm minimization
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.