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Fast design of efficient dictionaries for sparse representations

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)

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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: 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

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