Rusu, Cristian Fast design of efficient dictionaries for sparse representations. In: IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2012. IEEE, pp. 1-5. ISBN 978-1-4673-1025-3 (2012)
Full text not available from this repository.Abstract
One of the central issues in the field of sparse representations is the design of overcomplete dictionaries with a fixed sparsity level from a given dataset. This article describes a fast and efficient procedure for the design of such dictionaries. The method implements the following ideas: a reduction technique is applied to the initial dataset to speed up the upcoming procedure; the actual training procedure runs a more sophisticated iterative expanding procedure based on K-SVD steps. Numerical experiments on image data show the effectiveness of the proposed design strategy.
| Item Type: | Book Section |
|---|---|
| Identification Number: | https://doi.org/10.1109/MLSP.2012.6349795 |
| Uncontrolled Keywords: | K-SVD algorithm, T-mindot, clustering, large datasets training, representation errors, signal processing, sparse representations |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Research Area: | Computer Science and Applications |
| Depositing User: | Users 45 not found. |
| Date Deposited: | 07 Mar 2013 13:30 |
| Last Modified: | 12 Mar 2013 14:58 |
| URI: | http://eprints.imtlucca.it/id/eprint/1528 |
Actions (login required)
 |
Edit Item |
