NORMA eResearch @NCI Library

Block orthonormal overcomplete dictionary learning

Rusu, Cristian and Dumitrescu, Bogdan (2013) Block orthonormal overcomplete dictionary learning. In: 21st European Signal Processing Conference (EUSIPCO 2013). IEEE, Marrakech, pp. 1-5. ISBN 9780992862602

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In the field of sparse representations, the overcomplete dictionary learning problem is of crucial importance and has a growing application pool where it is used. In this paper we present an iterative dictionary learning algorithm based on the singular value decomposition that efficiently construct unions of orthonormal bases. The important innovation described in this paper, that affects positively the running time of the learning procedures, is the way in which the sparse representations are computed - data are reconstructed in a single orthonormal base, avoiding slow sparse approximation algorithms - how the bases in the union are used and updated individually and how the union itself is expanded by looking at the worst reconstructed data items. The numerical experiments show conclusively the speedup induced by our method when compared to previous works, for the same target representation error.

Item Type: Book Section
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions: School of Computing > Staff Research and Publications
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 03 Jul 2018 11:12
Last Modified: 03 Jul 2018 11:12

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