Name
Abstract | ||
|---|---|---|
Encouraging recent results in compressed sensing or compressive sampling suggest that a set of inner products with random measure- ment vectors forms a good representation of a source vector that is known to be sparse in some� xed basis. With quantization of these inner products, the encoding can be considered universal for sparse signals with known sparsity level. We analyze the operational rate- distortion performance of such source coding both with genie-aided knowledge of the sparsity pattern and maximum likelihood estima- tion of the sparsity pattern. We show that random measurements induce an additive logarithmic rate penalty, i.e., at high rates the performance with rate R + O(log R) and random measurements is equal to the performance with rate R and deterministic measure- ments matched to the source. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICASSP.2007.366822 | Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference |
Keywords | Field | DocType |
maximum likelihood estimation,rate distortion theory,signal representation,signal sampling,source coding,compressed sensing,compressive sampling,genie-aided knowledge,maximum likelihood estimation,random measurement vectors,rate-distortion performance,source coding,source vector representation,sparse signals,sparsity pattern,compressed sensing,eigenvalue distribution,quantization,random matrices,subspace detection | Mathematical optimization,Pattern recognition,Source code,Artificial intelligence,Sampling (statistics),Logarithm,Quantization (signal processing),Rate–distortion theory,Compressed sensing,Mathematics,Encoding (memory),Random matrix | Conference |
Volume | ISSN | ISBN |
3 | 1520-6149 | 1-4244-0727-3 |
Citations | PageRank | References |
34 | 2.87 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alyson K. Fletcher | 1 | 552 | 41.10 |
| Sundeep Rangan | 2 | 3101 | 163.90 |
| Vivek K. Goyal | 3 | 2031 | 171.16 |