摘要
针对非线性、非平稳信号的降噪问题,提出一种基于经验模式分解和过零检测的自适应降噪方法。经验模式分解可以把信号自适应分解成多个基本模式分量和一个余项的和,此过程等效于用一组带通滤波器对信号进行滤波。以过零率作为噪声评判准则,对经验模式分解结果进行重构,可实现信号的自适应降噪。应用实例表明该方法的有效性和广泛的应用潜力。
Aiming at the problem of nonlinear and nonstationary signal denoising,a novel adaptive denoising method based on Empirical Mode Decomposition(EMD) and zero-crossing detection is proposed.EMD method can decompose the signal into several Intrinsic Mode Functions (IMF) and a remainder,which equals to filter signal with a set of band-pass filters.Zero-pass ratio is used as the criterion to distinguish which compositions are noises,and noise can be got rid of adaptively.The successful application results show that the presented method is effective and has great potential in signal processing.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第26期184-186,222,共4页
Computer Engineering and Applications
基金
国家自然科学基金( the National Natural Science Foundation of China under Grant No50675153)
天津市自然科学基金( the NaturalScience Foundation of Tianjin City of China under Grant No07JCYBJC04600)
关键词
信号
经验模式分解
过零检测
降噪
signal
Empirical Mode Decomposition(EMD)
zero-pass detection
denoising