L1 optimization for robust signal processing

Shi, Mingren and Lukas, Mark A. (2005) L1 optimization for robust signal processing. In: 18th National ASOR Conference, 26-30 Nov 2005, Perth, WA.

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Abstract

In this paper we develop special methods using the active set frameworkof the reduced gradient algorithm (RGA) to solve discrete L1 optimization problemswith a single linear equality constraint sT x = g, or a sequence of such problems withdifferent s = si and g = gi. These problems arise in certain large robust signal process-ing problems. The sequence of problems is solved recursively using ideas of sensitivityanalysis, by regarding the next problem as a perturbation of the previous problem. Thenumerical experiments illustrate that the proposed methods work very efficiently.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: No evidence of copyright restrictions.
Depositing User: epEditor USQ
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 02 Sep 2008 04:29
Last Modified: 02 Jul 2013 22:34
Uncontrolled Keywords: L1 norm optimization; least absolute deviations; robust signal processing; active set; reduced gradient algorithm
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080202 Applied Discrete Mathematics
09 Engineering > 0906 Electrical and Electronic Engineering > 090609 Signal Processing
01 Mathematical Sciences > 0101 Pure Mathematics > 010104 Combinatorics and Discrete Mathematics (excl. Physical Combinatorics)
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970101 Expanding Knowledge in the Mathematical Sciences
URI: http://eprints.usq.edu.au/id/eprint/786

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