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.
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|
|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|
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