Performance Bounds on Sparse Representations Using Redundant Frames

dc.creatorAkçakaya, Mehmet
dc.creatorTarokh, Vahid
dc.date2007-03-09
dc.date.accessioned2026-07-07T08:17:07Z
dc.date.available2026-07-07T08:17:07Z
dc.descriptionWe consider approximations of signals by the elements of a frame in a complex vector space of dimension $N$ and formulate both the noiseless and the noisy sparse representation problems. The noiseless representation problem is to find sparse representations of a signal $\mathbf{r}$ given that such representations exist. In this case, we explicitly construct a frame, referred to as the Vandermonde frame, for which the noiseless sparse representation problem can be solved uniquely using $O(N^2)$ operations, as long as the number of non-zero coefficients in the sparse representation of $\mathbf{r}$ is $εN$ for some $0 \le ε\le 0.5$, thus improving on a result of Candes and Tao \cite{Candes-Tao}. We also show that $ε\le 0.5$ cannot be relaxed without violating uniqueness. The noisy sparse representation problem is to find sparse representations of a signal $\mathbf{r}$ satisfying a distortion criterion. In this case, we establish a lower bound on the trade-off between the sparsity of the representation, the underlying distortion and the redundancy of any given frame.
dc.description8 pages, 1 figure, Submitted to IEEE Transactions on Signal Processing
dc.identifierhttps://arxiv.org/abs/cs/0703045
dc.identifierhttp://arxiv.org/abs/cs/0703045
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/134014
dc.subjectInformation Theory
dc.titlePerformance Bounds on Sparse Representations Using Redundant Frames
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