| Paper: | SPTM-P9.6 | ||
| Session: | Nonlinear Systems and Signal Processing | ||
| Time: | Thursday, May 20, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing Theory and Methods: Nonlinear Systems and Signal Processing | ||
| Title: | A FAST MAXIMUM LIKELIHOOD ESTIMATION APPROACH TO LAD REGRESSION | ||
| Authors: | Yinbo Li; University of Delaware | ||
| Gonzalo Arce; University of Delaware | |||
| Abstract: | In this paper, we show that the optimization needed to solve theLAD regression problem can be viewed as a sequence of MaximumLikelihood estimates (MLE) of location. The derived algorithmreduces to an iterative procedure where a simple coordinatetransformation is applied during each iteration to direct theoptimization procedure along edge lines of the cost surface,followed by a MLE estimate of location which is executed by aweighted median operation. Requiring weighted medians only, thenew algorithm can be easily modularized for hardwareimplementation, as opposed to most of the other existing LADmethods which require complicated operations such as matrix entry manipulations. The new algorithm provides a better trade-off solution between convergence speed and implementation complexity compared to existing algorithms. | ||
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