计算机技术与发展2012，Vol.22Issue(2)：22-24,28,4.
基于局部积分均值的经验模态分解改进算法
Improved Algorithm for Empirical Mode Decomposition Based on Local Integral Mean
摘要
Abstract
The end effect and mode mixing is the main problem in the application of the empirical mode decomposition (EMD) method. The principles of standard EMD algorithm and the method of empirical mode decomposition based on local integral mean are introduced, and the advanced method of empirical mode decomposition based on local integral mean is presented. The method finds the best correlative sequence in the inner data and adopts the optimum sequence to proofread the fixing line near the ends of the data, and use the proofread fixing line into the sifting process of the algorithm. The simulation results show the method is effective in restraining end effect and mode mixing.关键词
经验模态分解/局部积分均值/端点效应/模态混叠Key words
empirical mode decomposition/local integral mean/end effect/mode mixing分类
信息技术与安全科学引用本文复制引用
杨庆,陈桂明,薛冬林..基于局部积分均值的经验模态分解改进算法[J].计算机技术与发展,2012,22(2):22-24,28,4.基金项目
军队科研项目(2009046) （2009046）
