IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
Sparsity Regularized Affine Projection Adaptive Filtering for System Identification
Young-Seok CHOI
Author information
JOURNAL FREE ACCESS

2014 Volume E97.D Issue 4 Pages 964-967

Details
Abstract

A new type of the affine projection (AP) algorithms which incorporates the sparsity condition of a system is presented. To exploit the sparsity of the system, a weighted l1-norm regularization is imposed on the cost function of the AP algorithm. Minimizing the cost function with a subgradient calculus and choosing two distinct weightings for l1-norm, two stochastic gradient based sparsity regularized AP (SR-AP) algorithms are developed. Experimental results show that the SR-AP algorithms outperform the typical AP counterparts for identifying sparse systems.

Content from these authors
© 2014 The Institute of Electronics, Information and Communication Engineers
Previous article Next article
feedback
Top