Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 8
2517-2521

Research of small-sample-size based on hyperbolic cosine matrix discriminant analysis

Ran Ruisheng1a
Zhang Shougui1b
Ren Yinshan2
Fang Bin3
1. a. College of Computer & Information Science, b. College of Mathematical Science, Chongqing Normal University, Chongqing 401331, China
2. Harbin Institute of Technology Robot Group Chongqing Yun'an Technology Co. , Ltd. , Chongqing 400039, China
3. College of Computer Science, Chongqing University, Chongqing 400044, China
DOI: 10.19734/j.issn.1001-3695.2019.01.0099

Abstract

Linear discriminant analysis(LDA) was a classical approach in pattern recognition, but LDA has the so-called small-sample-size(SSS) problem. To address this problem, this paper presented a hyperbolic cosine matrix discriminant analysis, named as HCDA. On the basis of hyperbolic cosine function, this paper first gave the definition and eigen-system of hyperbolic cosine matrix function, and then based on the characteristics of hyperbolic cosine matrix function eigen-system, it was introduced into LDA. HCDA had two superiorities. First, HCDA had no SSS problem and then it could extract more discriminant information. Second, there was an implicit mapping of samples. The mapping had a diffusion effect on the distance between samples, and the diffusion scale to the between-class distance was larger than that to the within-class distance. The experiment results on the handwritten digit, handwritten letter and Georgia Tech face databases show that, HCDA gets more advantageous recognition performance compared to the representative methods to solve the small-sample-size problem of LDA.

Foundation Support

国家自然科学基金资助项目(61876026)
教育部人文社会科学研究项目(20YJAZH084)
重庆市基础研究与前沿探索研究资助项目(cstc2016jcyjA0419,cstc2017jcyjAX0316)
重庆师范大学校级科研项目(16XLB006,16XZH07)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.01.0099
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 8
Section: Technology of Graphic & Image
Pages: 2517-2521
Serial Number: 1001-3695(2020)08-059-2517-05

Publish History

[2020-08-05] Printed Article

Cite This Article

冉瑞生, 张守贵, 任银山, 等. 基于双曲余弦矩阵鉴别分析的小样本问题研究 [J]. 计算机应用研究, 2020, 37 (8): 2517-2521. (Ran Ruisheng, Zhang Shougui, Ren Yinshan, et al. Research of small-sample-size based on hyperbolic cosine matrix discriminant analysis [J]. Application Research of Computers, 2020, 37 (8): 2517-2521. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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