| Paper: | DISPS-P1.11 | ||
| Session: | VLSI Algorithms and Architectures for DSP | ||
| Time: | Friday, May 21, 09:30 - 11:30 | ||
| Presentation: | Poster | ||
| Topic: | Design and Implementation of Signal Processing Systems: Fast Algorithms | ||
| Title: | A SPARSE SOLUTION TO THE BOUNDED SUBSET SELECTION PROBLEM: A NETWORK FLOW MODEL APPROACH | ||
| Authors: | Masoud Alghoniemy; University of Alexandria | ||
| Ahmed Tewfik; University of Minnesota | |||
| Abstract: | We reformulate the problem of finding the sparsest representationof a given signal using an overcomplete dictionary as a boundederror subset selection problem. Specifically, the reconstructedsignal is allowed to differ from the original signal by a boundederror. We argue that this bounded error formulation is natural inmany applications, such as coding. Our novel formulationguarantees the sparsest solution to the bounded error subsetselection problem by minimizing the number of nonzerocoefficients in the solution vector. We show that this solution can be computed by finding the minimum cost flow path of anequivalent network. Integer programming is adopted to find thesolution. | ||
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