经验模式分解与小波变换在模拟信号中的对比分析  

Comparison analysis of empirical mode decomposition and wavelet decomposition in analog signals

作　　者：李旋[1] 周清锋[1] 何朝津[1] 杨礼平[1] 赵立科[1] 王晓辉[1] 

机构地区：[1]江苏省地质调查研究院,江苏南京210018

出　　处：《地质学刊》2009年第1期79-83,共5页Journal of Geology

摘　　要：经验模式分解和小波分解是当前有效处理非平稳信号的两种时频分析方法,它们各具优缺点,适用于不同的领域。模拟信号突变性检测、趋势检测和频率检测的对比实验表明:在突变检测方面,小波分解优于经验模式分解;但经验模式分解在低频信号检测及趋势检测方面优于小波分解。Empirical mode decomposition （EMD） and wavelet decomposition （ WD ） are two new time-frequency analytic methods used to analyze the non-stationary signal. Each of these two analytic methods holds its characteristics in non-stationary signal processing. A contrast experiment among simulated experiments of signal mutation, signal trend extraction and frequency detection demonstrated that WD was better than EMD in signal mutation detection, while EMD was better than WD in low frequency signal detection and signal trend extraction.

关 键 词：经验模式分解 小波分解 非平稳信号 时频分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] O174.22[自动化与计算机技术—计算机科学与技术]