| 核方法与流形学习在心电识别中的研究 |
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| 引用本文： | 李学华,舒兰.核方法与流形学习在心电识别中的研究[J].计算机工程与应用,2009,45(20):20-22. |
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| 作者姓名： | 李学华 舒兰 |
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| 作者单位： | 电子科技大学 应用数学学院，成都 610054 |
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| 摘 要： | 结合核方法和局部线性嵌入（LLE）方法，提出了一种基于核局部线性嵌入方法，该方法克服了局部线性嵌入方法由于心电特征分布不均衡造成的不稳定问题。结合支持向量机在MIT-BIH心律失常标准数据库进行实验，并利用PCA和LLE进行特征提取比较，验证了该方法的有效性及优势。
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| 关 键 词： | 核方法 局部线性嵌入 支持向量机 心电图识别 |
| 收稿时间： | 2009-3-31 |
| 修稿时间： | 2009-5-5
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Research of kernel method and manifold learning for ECG recognition |
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| LI Xue-hua,SHU Lan.Research of kernel method and manifold learning for ECG recognition[J].Computer Engineering and Applications,2009,45(20):20-22. |
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| Authors: | LI Xue-hua SHU Lan |
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| Affiliation: | School of Applied Mathematics，University of Electronic Science and Technology of China，Chengdu 610054，China |
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| Abstract: | This paper investigates kernel method and Locally Linear Embedding ( LLE) for proposed kernel method based locally linear embedding features extraction algorithm.The proposed kernel method based locally linear embedding overcomes the instability of locally linear embedding caused by incongruous ECG features distribution.Furthermore,this paper has realized the emulation experiments of MIT-BIH ECG Arrhythmias data base combining with support vector machine.A full comparison of features extraction by PCA and L... |
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| Keywords: | kernel method locally linear embedding support vector machine ECG recognition |
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