| 摘 要: 主成分分析是一种非常有效的数据分析处理的技术，具有非常广泛的应用前景。本文首先概述了主成分分 析方法，然后介绍了PCA的定义、模型、算法及选取主成分个数的标准，对PCA技术的优势和缺陷分别进行了剖析和 总结，对PCA在评价排序、特征提取、模式识别、图像处理、图像分类和图像压缩等领域的实际应用进行了讨论，对主 成分分析方法的发展趋势和应用前景做了展望。 |
| 关键词: 主成分分析；PCA模型；特征提取；图像处理 |
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中图分类号: TP391
文献标识码: A
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| 基金项目: 陕西省教育厅专项科研计划项目(15JK1803)，咸阳师范学院专项科研基金资助项目(13XSYK055). |
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| A Review of Principal Component Analysis |
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ZHAO Qiang
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( School of Computing Science, Xianyang Normal University, Xianyang 712000, China)
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| Abstract: PCA(Principal Component Analysis)is an effective data analysis technique with a bright future of extensive application.The paper summarizes PCA in the first place,and then introduces its definition,data model,algorithm and the standards to determine the number of selected principal components.Moreover,the paper analyzes and summarizes the advantages and disadvantages of the PCA technique,and discusses its practical application in different fields,like evaluation and sorting,feature extraction,patter recognition,image processing,image classification and image compression.Finally,the paper makes expectation about the development trend and application prospect. |
| Keywords: PCA;PCA model;feature extraction;image processing |
