摘要
为解决模态混叠问题,将总体经验模态分解方法应用于水文时间序列的多尺度研究中.将白噪声加入原始序列,经过总体经验模态分解后得到固有模态函数,通过对结果进行显著性检验并最终得到水文时间序列主要振荡周期、中心频率、平均振幅等信息.通过对黄河三门峡水文站实测天然年径流序列进行分析,发现总体经验模态分解能够较好地解决模态混叠现象;同时与小波分析方法对比,该方法较之传统的经验模态分解具有更高的精度,能够应用于水文时间序列多尺度分析研究.
The ensemble empirical mode decomposition was used for the multi-scale analysis of hydrological time series.Through this approach,the white noise-added data could be decomposed into several intrinsic mode function components.The main oscillation period,center frequency and mean amplitude were extracted through the significance test.This method was applied to analyze the natural runoff hydrological sequence of Yellow River Sanmen Gorge Station.The results show that the mode mixing problem could be solved by this approach.To contrast with the traditional empirical mode decomposition,the ensemble empirical mode decomposition can improve the analysis precision,and provide a analytic method to hydrological time series multi-scale research.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第11期105-108,121,共5页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(40901022)
关键词
水文序列
总体经验模态分解
模态混叠
希尔波特-黄变换
多尺度分析
hydrology sequence
ensemble empirical mode decomposition（EEMD）
mode mixing
Hilbert-Huang transform
multi-scale analysis
