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L1 optimization for robust signal processing
Conference presentation

L1 optimization for robust signal processing

M. Shi and M.A. Lukas
18th National Conference of the Australian Society for Operations Research (ASOR) & 11th Australian Optimisation Day (Perth, Western Australia, 26/09/2005–28/09/2005)
2005

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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