| 独立分量分析和小波熵在动作模式分类中的应用 |
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| 引用本文： | 颜志国,王志中,任晓梅.独立分量分析和小波熵在动作模式分类中的应用[J].北京生物医学工程,2006,25(5):457-460,465. |
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| 作者姓名： | 颜志国 王志中 任晓梅 |
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| 作者单位： | 上海交通大学生物医学工程系,上海,200030;上海交通大学生物医学工程系,上海,200030;上海交通大学生物医学工程系,上海,200030 |
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| 基金项目： | 国家重点基础研究发展计划(973计划) |
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| 摘 要： | 在表面肌电信号(electromyography,EMG)中,各类动作的识别是一个重要研究方向.本文采用独立分量分析independent component analysis,ICA)对肌电信号进行处理,消除各动作信号之间的相互线性耦合叠加,并采用信号的小波熵作为特征向量进行模式识别.试验表明,在对信号进行先期ICA处理以后,动作模式的识别效果较好.此方法也可应用于其他生理信号的识别分类.
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| 关 键 词： | 独立分量分析 模式识别 小波包 小波熵 |
| 文章编号： | 1002-3208（2006）05-0457-04 |
| 收稿时间： | 2005-06-01 |
| 修稿时间： | 2005-06-01 |
The Application of the ICA and the Wavelet Entropy in Motion Recognition |
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| YAN Zhiguo,WANG Zhizhong,REN Xiaomei.The Application of the ICA and the Wavelet Entropy in Motion Recognition[J].Beijing Biomedical Engineering,2006,25(5):457-460,465. |
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| Authors: | YAN Zhiguo WANG Zhizhong REN Xiaomei |
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| Affiliation: | Department of Biomedical Engineering, Shanghai Jiaotong University, Shanghai 200030 |
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| Abstract: | For the electromyography(EMG) processing,the motions recognition is a hot domain.The independent component analysis(ICA) is used to pre-process and decouple the EMG signals.The wavelet entropy of the EMG signals are executed as the characterization vectors.Using the characterization vectors as the input and training the neural networks,we can get an excellent classifier with good performance.The result shows that the motions pattern recognition with signals pre-processed by ICA is better than that before decoupling the EMG. |
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| Keywords: | EMG pattern recognition wavelet packet wavelet entropy |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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