计算机工程与应用Issue(3)：222-228,7.DOI:10.3778/j.issn.1002-8331.1305-0500
改进的LS-SVM方法在EMD端点效应问题中的应用
Application of improved LS-SVM method in end effect of EMD
摘要
Abstract
The empirical mode decomposition is an effective method for non-stationary and nonlinear signals processing, but at the same time it produces endpoint effects which would decrease the decomposition accuracy when the three order spline interpolation is used repeatedly. In order to suppress the endpoint effect in empirical mode decomposition, this paper proposes an approach based on least squares support vector machine and mirror extension. In this new method, by using LS-SVM to the original signal sequence it would produce a finite number of extensional data points at both ends, and then with mirror extension acting on the extensional data a symmetrical continuation signal sequence would be formed. Then a ring signal sequence would be produced after the end extension and mirror extension. The empirical mode decomposition is used to deal with the ring signal sequence. By analyzing the simulation signals and real EEG signals with the new method, the results show that the method can effectively restrain the endpoint effect. And compared with other extension methods, it is better than Support Vector Machine(SVM), and the Least Squares Support Vector Machine(LS-SVM).关键词
经验模态分解/端点效应/最小二乘支持向量机/镜像延拓/支持向量机Key words
empirical mode decomposition/end effect/Least Squares Support Vector Machine(LS-SVM)/mirror exten-sion/Support Vector Machine(SVM)分类
信息技术与安全科学引用本文复制引用
徐志军,旷欢,王如龙,华保健..改进的LS-SVM方法在EMD端点效应问题中的应用[J].计算机工程与应用,2015,(3):222-228,7.基金项目
国家高技术研究发展计划（863）（No.2009AA010314）。 （）
