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  2018, Vol. 31 Issue (6): 505-515    DOI: 10.16451/j.cnki.issn1003-6059.201806003
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Incremental Non-negative Matrix Factorization Based on Fisher Discriminant Analysis
CAI Jing1,2,3, WANG Wanliang1, ZHENG Jianwei1, LUO Zhijian3, SHEN Si1,2
1.College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310014
2.Department of Forensic Science and Technology, Zhejiang Police College, Hangzhou 310053
3.College of Computer Science and Technology, Zhejiang University, Hangzhou 310027

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Abstract  

Incremental non-negative matrix factorization is an unsupervised learning algorithm based on subspace dimensionality reduction technology. In this paper, the idea of fisher discriminant analysis is introduced into incremental non-negative matrix factorization, and an incremental learning algorithm of non-negative matrix factorization with discriminative information and constraints is proposed. Firstly, prior information of original training samples is utilized to initialize the incremental coefficient matrix through an index matrix. Secondly, the object function of incremental non-negative matrix factorization is improved to be a batch-incremental learning algorithm with the constraints of maximizing between-class scatter and minimizing within-class scatter. Finally, the factor matrices are calculated by the method of multiplicative iteration. Experimental results on ORL, Yale B and PIE face databases show the effectiveness of the proposed method.

Received: 09 March 2018     
ZTFLH: TP 391.4  
Fund:

Supported by National Key Research and Development Program of China(No.2017YFC0803700), National Natural Science Foundation of China(No.61602413), Zhejiang Provincial Educational Commission of China(No.Y201431023), Zhejiang Provincial Domestic Visiting Scholars Project for College Teachers' Professional Development(No.FX2017069)

About author:: (CAI Jing(Corresponding author), Ph.D. candidate, lecturer. His research interests include image processing and machine lear-ning.)(WANG Wanliang, Ph.D., professor. His research interests include intelligent algorithms and network control.)(ZHENG Jianwei, Ph.D., associate profe-ssor. His research interests include machine learning and feature extraction.)(LUO Zhijian, Ph.D. candidate. His research interests include pattern recognition and computer vision.)(SHEN Si, Ph.D. candidate, lecturer. Her research interests include machine learning and intelligent transportation.)
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CAI Jing
WANG Wanliang
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LUO Zhijian
SHEN Si
Cite this article:   
CAI Jing,WANG Wanliang,ZHENG Jianwei等. Incremental Non-negative Matrix Factorization Based on Fisher Discriminant Analysis[J]. , 2018, 31(6): 505-515.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201806003      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I6/505
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