Abolghasemi, V, Chen, M, Alameer, A 
ORCID: https://orcid.org/0000-0002-7969-3609, Ferdowsi, S, Chambers, J and Nazarpour, K
2018,
'Incoherent dictionary pair learning : application to a novel open-source database of chinese numbers'
, IEEE Signal Processing Letters, 25 (4)
, pp. 472-476.
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Abstract
We enhance the efficacy of an existing dictionary pair learning algorithm by adding a dictionary incoherence penalty term. After presenting an alternating minimization solution, we apply the proposed incoherent dictionary pair learning (InDPL) method in classification of a novel open-source database of Chinese numbers. Benchmarking results confirm that the InDPL algorithm offers enhanced classification accuracy, especially when the number of training samples is limited.
| Item Type: | Article |
|---|---|
| Schools: | Schools > School of Computing, Science and Engineering |
| Journal or Publication Title: | IEEE Signal Processing Letters |
| Publisher: | IEEE |
| ISSN: | 1070-9908 |
| Depositing User: | A Alameer |
| Date Deposited: | 09 Jun 2022 14:53 |
| Last Modified: | 13 Jun 2022 09:40 |
| URI: | http://usir.salford.ac.uk/id/eprint/63749 |
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