| 应用小波包变换和主成分分析识别亚健康状态 |
| |
| 引用本文： | 张爱华,孔令杰.应用小波包变换和主成分分析识别亚健康状态[J].计算机工程与应用,2011,47(26):238-241. |
| |
| 作者姓名： | 张爱华 孔令杰 |
| |
| 作者单位： | 兰州理工大学电气工程与信息工程学院,兰州,730050 |
| |
| 基金项目： | 国家自然科学基金No.30670529~~ |
| |
| 摘 要： | 为了评估亚健康状态,提出一种基于心电信号小波包变换和主成分分析的亚健康状态识别新方法。采用小波包变换对心电信号进行特征提取;再利用主成分分析(PCA)对所提特征进行降维处理,以剔除特征之间的冗余信息;最后应用线性判别式分析(LDA)对亚健康状态进行分类识别。研究结果显示,该方法能获得较高的识别率,对于实现亚健康状态的评估具有一定的参考价值。
|
| 关 键 词： | 亚健康状态 心电信号 小波包变换 主成分分析 线性判别式分析 |
| 修稿时间： | |
Wavelet packet transform and principal component analysis for identifying sub-health state |
| |
| ZHANG Aihua,KONG Lingjie.Wavelet packet transform and principal component analysis for identifying sub-health state[J].Computer Engineering and Applications,2011,47(26):238-241. |
| |
| Authors: | ZHANG Aihua KONG Lingjie |
| |
| Affiliation: | ZHANG Aihua,KONG Lingjie School of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China |
| |
| Abstract: | In order to evaluate sub-health state,a new sub-health state recognition method based on wavelet packet transform and Principal Component Analysis(PCA) of ECG signals is discussed.The features of ECG signals are extracted by using wavelet packet transform,and the dimension of the features is reduced by utilizing PCA for removing the redundant information between them.Finally,Linear Discriminant Analysis(LDA) is applied on sub-health state recognition.The results demonstrate that this method can get higher r... |
| |
| Keywords: | sub-health state ECG signals wavelet packet transform Principal Component Analysis(PCA) Linear Discriminant Analysis(LDA) |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《计算机工程与应用》浏览原始摘要信息 |
|
点击此处可从《计算机工程与应用》下载全文 |
