Non-convex optimization for the design of sparse FIR filters
Name
Wei-2009-Non-convex optimization for the design of sparse FIR filters.pdf
Size
139.45 KB
Format
Adobe PDF
Checksum (MD5)
e1de47ab1f27e1062703e6df5220b1e3
Author(s)
Wei, Dennis
Date Issued
October 2009
Journal
IEEE/SP 15th Workshop on Statistical Signal Processing, 2009. SSP '09
Publisher
Institute of Electrical and Electronics Engineers
Citation
Wei, D. “Non-convex optimization for the design of sparse fir filters.” Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on. 2009. 117-120. © 2009 Institute of Electrical and Electronics Engineers
Version
Final published version
Abstract
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.
Subjects
FIR digital filters
Sparse filters
non-convex optimization
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/SSP.2009.5278626
