小波阈值启发的EMD降噪新方法  

Wavelet threshold noise EMD inspired a new method

作　　者：何婷[1] 常勇[2] 

机构地区：[1]甘肃省畜牧工程职业技术学院电子信息工程系,甘肃武威733006 [2]兰州石化职业技术学院电子电气工程系,甘肃兰州730060

出　　处：《自动化与仪器仪表》2014年第11期70-74,77,共6页Automation & Instrumentation

摘　　要：目前经验模态分解(Empirical Mode Decomposition-EMD)的作用之一就是对非平稳信号进行去噪,而之前小波阈值去噪长期以来一直是在这一领域占主导地位。本文就是将小波阈值去噪的原理泛化到经验模态分解中,然后采用EMD方法进行含噪声信号降噪,实验结果表明虽然小波阈值去噪这一原理不能直接应用于EMD,但可以适当地的改进以适应EMD模式分解的特殊性。在同样的方法中,受平移不变小波阈值的启发,对EMD采用相似的方法进行研究,从而增强其去噪性能。One of the tasks for which empirical mode decomposition（EMD） is potentially useful is nonparametric signal dennis- ing, an area for which wavelet thresholding has been the dominant technique for many years. In this paper, the wavelet thresholding principle is used in the decomposition modes resulting from applying EMD to a signal. We show that although a direct application of this principle is not feasible in the EMD case, it can be appropriately adapted by exploiting the special characteristics of the EMD de- composition modes. In the same manner, inspired by the translation invariant wavelet thresholding, a similar technique adapted to EMD is developed, leading to enhanced denoising performance.

关 键 词：经验模态分解(EMD) 信号降噪 小波阈值 

分 类 号：TP23[自动化与计算机技术—检测技术与自动化装置]