An adaptive extreme learning machine algorithm and its application on face recognition

被引:4
作者
Ni, Jian [1 ]
Xu, Xinzheng [1 ]
Ding, Shifei [1 ]
Sun, Tongfeng [1 ]
机构
[1] China Univ Min & Technol, Sch Comp Sci & Technol, 1 Daxue Rd, Xuzhou, Jiangsu, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
extreme learning machine; ELM; AP clustering algorithm; classification; face recognition;
D O I
10.1504/IJCSM.2015.073601
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
As a fast iterative neural networks learning algorithm, extreme learning machine (ELM) is a fast learning computation approach, and its whole learning process is completed through a mathematical transformation. However, the number of hidden layer neurons generally requires manual definition. In this paper, we propose an adaptive extreme learning machine (AP-ELM) algorithm which automatically determines the number of hidden layer neurons based on the AP clustering algorithm. In proposed algorithm, the samples are clustered through the AP clustering algorithm and then the number of cluster centres is used to determine the number of hidden layer neurons. Finally, the proposed adaptive ELM algorithm is used to face recognition. Experimental results verify that AP-ELM has good accuracy and reliability.
引用
收藏
页码:611 / 619
页数:9
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