自动化学报2017，Vol.43Issue(5)：835-842,8.DOI:10.16383/j.aas.2017.c160299
一种快速的多个主成分并行提取算法
A Fast Algorithm That Extracts Multiple Principle Components in Parallel
摘要
Abstract
Principle component analysis is a powerful tool in signal processing and data analysis. Up to now, some existing algorithms for multiple principal components extraction have a slow convergence speed. In order to solve this problem, a faster convergence algorithm is proposed, which can extract multiple principal components from the input signal in parallel. The equilibrium point analysis method and stochastic discrete time method are adopted to analyze the convergence and self-stabilizing property of the proposed algorithm. Simulation results show that compared with some existing algorithms, the proposed algorithm not only has a faster convergence speed but also has a higher estimating accuracy.关键词
主成分分析/并行提取/自稳定性/神经网络Key words
Principle component analysis/extraction in parallel/self-stabilizing property/neural networks引用本文复制引用
孔令智,高迎彬,李红增,张华鹏..一种快速的多个主成分并行提取算法[J].自动化学报,2017,43(5):835-842,8.基金项目
国家自然科学基金(61374120, 61673387), 陕西省自然科学基金(2016JM6015) 资助 Supported by National Natural Science Foundation of China(61374120, 61673387), Natural Science Foundation of Shaanxi Province(2016JM6015) （61374120, 61673387）
