By Topic

Non-convex optimization for the design of sparse fir filters

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Dennis Wei ; Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 77 Massachusetts Avenue, Cambridge, 02139, USA

This paper presents a method for designing sparse FIR filters by means of a sequence of p-norm minimization problems with p gradually decreasing from 1 toward 0. The lack of convexity for p < 1 is partially overcome by appropriately initializing each subproblem. A necessary condition of optimality is derived for the subproblem of p-norm minimization, forming the basis for an efficient local search algorithm. Examples demonstrate that the method is capable of producing filters approaching the optimal level of sparsity for a given set of specifications.

Published in:

2009 IEEE/SP 15th Workshop on Statistical Signal Processing

Date of Conference:

Aug. 31 2009-Sept. 3 2009