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| A Generalized Principal Component Extraction Algorithm and Its Convergence Analysis |
| GAO Yingbin KONG Xiangyu HU Changhua ZHANG Huihui HOU Li’an |
| (The Second Artillery Engineer University, Xi’an 710025, China) |
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Abstract The generalized principal component analysis plays an important roles in many fields of modern signal processing. However, up to now, there are few algorithms, which can extract the generalized principal component adaptively. In this paper, a generalized principal component extraction algorithm, which has fast convergence speed, is proposed. The corresponding Deterministic Discrete Time (DDT) system of the proposed algorithm is analyzed and some conditions about the learning rate and initial weight vector are also obtained. Finally, computer simulation and practical application results show that compared with some existing algorithms, the proposed algorithm has faster convergence speed and higher estimation accuracy.
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Received: 17 December 2015
Published: 04 July 2016
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| Fund: The National Natural Science Foundation of China (61074072, 61374120), The National Science Fund for Distinguished Youth Scholars (61025014) |
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Corresponding Authors:
KONG Xiangyu
E-mail: xiangyukong01@163.com
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