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Clustering large datasets - Bounds and applications with K-SVD

Rusu, Cristian (2013) Clustering large datasets - Bounds and applications with K-SVD. UPB Scientific Bulletin, Series C: Electrical Engineering, 75 (2). pp. 31-40. ISSN 2286-3540

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This article presents a clustering method called T-mindot that is used to reduce the dimension of datasets in order to diminish the running time of the training algorithms. The T-mindot method is applied before the K-SVD algorithm in the context of sparse representations for the design of overcomplete dictionaries. Simulations that run on image data show the efficiency of the proposed method that leads to the substantial reduction of the execution time of K-SVD, while keeping the representation performance of the dictionaries designed using the original dataset.

Item Type: Article
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 10:54
Last Modified: 03 Jul 2018 10:54

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