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PCA(主成分分析)MATLAB代码

于 2022-10-14 发布 文件大小:444.05 kB
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PCA(主成分分析)算法被广泛应用于工程和科学研究中,本报告主要从PCA的基本结构和基本原理对其进行研究,常规的PCA算法主要采用线性算法,通过研究论证发现线性的PCA算法存在着许多不足,比如线性PCA算法不能从线性组合中把独立信号成分分离出来,主分量只由数据的二阶统计量—自相关阵确定,这种二阶统计量只能描述平稳的高斯分布等,因此必须对其进行改进,经改进后的PCA算法有非线性PCA算法、鲁棒算法等。我们通过PCA算法在直线(平面)中拟和的例子说明了PCA在工程中的应用。本例子采用的是成分分析中的次成分(方差最小的成分),通过对结果的分析,我们可以看出,利用PCA算法可以得到较好的拟和结果。

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