A New Feature Extraction Algorithm Based on Orthogonal Regularized Kernel CCA and Its Application
Joint Authors
Zeng, Fugeng
Guo, Xinchen
Fan, Xiuling
Xi, Xiantian
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-10-29
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Information Technology and Computer Science
Abstract EN
In this paper, an orthogonal regularized kernel canonical correlation analysis algorithm (ORKCCA) is proposed.
ORCCA algorithm can deal with the linear relationships between two groups of random variables.
But if the linear relationships between two groups of random variables do not exist, the performance of ORCCA algorithm will not work well.
Linear orthogonal regularized CCA algorithm is extended to nonlinear space by introducing the kernel method into CCA.
Simulation experimental results on both artificial and handwritten numerals databases show that the proposed method outperforms ORCCA for the nonlinear problems.
American Psychological Association (APA)
Guo, Xinchen& Fan, Xiuling& Xi, Xiantian& Zeng, Fugeng. 2018. A New Feature Extraction Algorithm Based on Orthogonal Regularized Kernel CCA and Its Application. Journal of Electrical and Computer Engineering،Vol. 2018, no. 2018, pp.1-5.
https://search.emarefa.net/detail/BIM-1184557
Modern Language Association (MLA)
Guo, Xinchen…[et al.]. A New Feature Extraction Algorithm Based on Orthogonal Regularized Kernel CCA and Its Application. Journal of Electrical and Computer Engineering No. 2018 (2018), pp.1-5.
https://search.emarefa.net/detail/BIM-1184557
American Medical Association (AMA)
Guo, Xinchen& Fan, Xiuling& Xi, Xiantian& Zeng, Fugeng. A New Feature Extraction Algorithm Based on Orthogonal Regularized Kernel CCA and Its Application. Journal of Electrical and Computer Engineering. 2018. Vol. 2018, no. 2018, pp.1-5.
https://search.emarefa.net/detail/BIM-1184557
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1184557