基于二进小波变换的奇异信号消噪
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摘要
小波变换在时、频两域均具有表征信号局部特征的能力,是描述和检测信号局部性质的有效手段;利用小波变换模极大值能检测出信号上的所有奇异点,根据小波变换模极大值随尺度的增、减规律,去除噪声对应的极值点,再由模极大值重构信号,提出了小波变换基于奇异信号的消噪方法,并应用于对一瞬时心率信号进行消噪。
Wavelet transform has the ability of expressing signal's singularity in time and frequency field,is an effective measurement to describe and detect signal's partial property.It can detect all singularity points of signals for utilizing modular maximum of wavelet transform.We can remove the noise maximum point,bases on the increase or decrease discipline of wavelet transform modular maximum along with scales,and use the modular maximum to reconstruct signal,put forward a de-noise method based on signal's singularity with wavelet transform,and apply it to de-noise a signal of heart rate.
Wavelet transform has the ability of expressing signal's singularity in time and frequency field,is an effective measurement to describe and detect signal's partial property.It can detect all singularity points of signals for utilizing modular maximum of wavelet transform.We can remove the noise maximum point,bases on the increase or decrease discipline of wavelet transform modular maximum along with scales,and use the modular maximum to reconstruct signal,put forward a de-noise method based on signal's singularity with wavelet transform,and apply it to de-noise a signal of heart rate.
引文
[1]彭玉华.小波变换与工程应用[M].北京:科学出版社,1999.
[2]胡昌华,李国华,刘涛,等.基于MATLAB的系统分析与设计——小波分析[M].西安:西安电子科技大学出版社,2004.
[3]张根昌,吴并臻,刘跃峰,等.小波分析技术在地震信号噪声处理中的应用[J].矿冶,2003,12(1):89-92.
[4]S.G.Mallat,Characterization of signals From Multi-scales Edges[J].NYU,Computer Science Tech.Report,1991.
[5]杨建平,阮文.基于小波包变换的图像消噪方法[J].井冈山师范学院学报,2005,26(3):17-19.
[2]胡昌华,李国华,刘涛,等.基于MATLAB的系统分析与设计——小波分析[M].西安:西安电子科技大学出版社,2004.
[3]张根昌,吴并臻,刘跃峰,等.小波分析技术在地震信号噪声处理中的应用[J].矿冶,2003,12(1):89-92.
[4]S.G.Mallat,Characterization of signals From Multi-scales Edges[J].NYU,Computer Science Tech.Report,1991.
[5]杨建平,阮文.基于小波包变换的图像消噪方法[J].井冈山师范学院学报,2005,26(3):17-19.
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