摘要
为了提取强背景噪声中淹没的微弱信号特征和避免信号奇异点附近的振荡现象,将平移不变引入多小波,提出一种基于平移不变多小波的降噪方法。多小波具有多个尺度函数和小波函数,具备单小波无法同时满足的优良性质,可以匹配信号中不同的特征信息,而平移不变多小波更有效地消除了Gibbs现象且其中的平均过程具有优越的消噪性并保持了信号的光滑性。实验证明,应用改进后的该方法能更好地逼近真实信号。
A new method of denoising based on translation-invariant multiwavelets is proposed to extract the features of the fault signal from strong background noise. Multiwavelets have several sealing functions and wavelet functions, possess the excellent properties that scalar wavelet cannot satisfy simultaneously, and match different characteristics of signals. Translation-invariant multiwavelets avoid Gibbs phenomena and their average process show superior denoising and main- tain signal smoothness. The experiments show this improved method is practicable.
出处
《国外电子测量技术》
2013年第10期5-7,共3页
Foreign Electronic Measurement Technology
基金
河南省科技厅基础与前沿项目(132300410361)
河南省教育厅资助课题2013-JSJYYB-140
关键词
多小波
平移不变
信号降噪
multiwavelets
translation-invariant
signal denoising
