| 基于最小二乘支持向量机的信号回归 |
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| 引用本文： | 徐立祥,余海峰,段宝彬,吴文静.基于最小二乘支持向量机的信号回归[J].合肥学院学报(自然科学版),2010,20(3):11-14. |
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| 作者姓名： | 徐立祥 余海峰 段宝彬 吴文静 |
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| 作者单位： | 合肥学院,数学与物理系,合肥,230601 |
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| 基金项目： | 合肥学院自然科学研究一般项目 |
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| 摘 要： | 基于支持向量机核函数的条件和Sobolev Hilbert空间H1(R;a,b)的再生核,提出了一种称为最小二乘支持向量机的新的回归模型,并将该回归模型应用于信号回归的仿真实验中.实验表明,最小二乘支持向量机的核函数采用再生核是可行的,它优于常用的高斯核函数.
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| 关 键 词： | 支持向量机 核函数 再生核 信号回归 |
The Signal Regression Based on Least Square Support Vector Machine |
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| XU Li-xiang,YU Hai-feng,DUAN Bao-bin,WU Wen-jing.The Signal Regression Based on Least Square Support Vector Machine[J].Journal of Hefei University :Natural Sciences,2010,20(3):11-14. |
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| Authors: | XU Li-xiang YU Hai-feng DUAN Bao-bin WU Wen-jing |
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| Institution: | XU Li-xiang,YU Hai-feng,DUAN Bao-bin,WU Wen-jing(Department of Mathematics and Physics,Hefei University,Hefei 230601,China) |
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| Abstract: | Based on the conditions of kernel function of support vector machine and the reproducing kernel on the Sobolev Hilbert space H1(R;a,b),the paper provides a new regression model which is called the least square reproducing kernel support vector machine,and applies the regression model to the simulation experiment of the signal regression.The experiment shows that the reproducing kernel which the least square support vector machine adopts is feasible,and better than the usual Gaussian kernel function. |
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| Keywords: | SVM kernel function reproducing kernel signal regression |
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