Subband Adaptive Filtering with -Norm Constraint for Sparse System Identification

Young-Seok Choi

Mathematical Problems in Engineering, 2013, vol. 2013, 1-7

Abstract:

This paper presents a new approach of the normalized subband adaptive filter (NSAF) which directly exploits the sparsity condition of an underlying system for sparse system identification. The proposed NSAF integrates a weighted -norm constraint into the cost function of the NSAF algorithm. To get the optimum solution of the weighted -norm regularized cost function, a subgradient calculus is employed, resulting in a stochastic gradient based update recursion of the weighted -norm regularized NSAF. The choice of distinct weighted -norm regularization leads to two versions of the -norm regularized NSAF. Numerical results clearly indicate the superior convergence of the -norm regularized NSAFs over the classical NSAF especially when identifying a sparse system.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2013/601623.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2013/601623.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:601623

DOI: 10.1155/2013/601623

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().