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吴跃

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期刊论文

Global Convergence Analysis of a PCA Learning Algorithm

吴跃Mao Ye Yue Wu and Zhang Yi

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摘要/描述

rincipal component analysis(PCA) by neural network is an adaptive statistical signal processing method which has many applications Since many PCA neural networks do not converge globally, it is nature to study the global convergence of PCA learning algorithm. In this paper, the previous works on the globally convergent PCA neural networks are presented first. Then based on the mismatch of previous PCA neural networks, we propose and analyze a PCA learning algorithm. This algorithm is convergent globally. And a rigorous mathematical proof is given. Simulation results show the efiiciency and effectiveness ofthis algorithm.

【免责声明】以下全部内容由[吴跃]上传于[2009年05月20日 11时32分51秒],版权归原创者所有。本文仅代表作者本人观点,与本网站无关。本网站对文中陈述、观点判断保持中立,不对所包含内容的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考,并请自行承担全部责任。

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