Name
Abstract | ||
|---|---|---|
Data are said to follow the transform (or analysis) sparsity model if they become sparse when acted on by a linear operator called a sparsifying transform. Several algorithms have been designed to learn such a transform directly from data, and data-adaptive sparsifying transforms have demonstrated excellent performance in signal restoration tasks. Sparsifying transforms are typically learned using... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TSP.2018.2883021 | IEEE Transactions on Signal Processing |
Keywords | DocType | Volume |
Transforms,Analytical models,Signal processing algorithms,Computational modeling,Sparse matrices,Convolution,Image reconstruction | Journal | 67 |
Issue | ISSN | Citations |
2 | 1053-587X | 2 |
PageRank | References | Authors |
0.35 | 24 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luke Pfister | 1 | 37 | 2.78 |
| Yoram Bresler | 2 | 1104 | 119.17 |