Sparse Representations are Most Likely to be the Sparsest Possible (2004)
by
Michael Elad
| Venue: | EURASIP Journal on Applied Signal Processing, Paper No. 96247 |
| Citations: | 7 - 1 self |
BibTeX
@INPROCEEDINGS{Elad04sparserepresentations,
author = {Michael Elad},
title = {Sparse Representations are Most Likely to be the Sparsest Possible},
booktitle = {EURASIP Journal on Applied Signal Processing, Paper No. 96247},
year = {2004},
pages = {1--12}
}
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Abstract
and a full rank matrix D with N < L, we define the signal's overcomplete representations as all # satisfying S = D#. Among all the possible solutions, we have special interest in the sparsest one -- the one minimizing 0 . Previous work has established that a representation is unique if it is sparse enough, requiring 0 < Spark(D)/2.
