摘要
为提高监护信息系统预报的准确性,提出一种强噪声下监护信息的降噪方法.该方法利用小波变换分析噪声和生理信号的小波系数的特点,应用Hampel滤波器对生理信号小波系数进行滤波处理,并将处理后信号进行小波逆变换,实现监护信息的降噪处理.选择PhysioNet数据库数据进行实验,结果表明文中方法对监护信息有较好的降噪效果.
In order to improve the accuracy of information prediction for monitoring systems,a denoising method of monitoring information under strong noise is proposed.In this method,the characteristics of wavelet coefficients of both the monitoring information and the noise are analyzed based on the wavelet transform,and the Hampel filtering is adopted to process the wavelet transform coefficients.Then,an inverse wavelet transform is performed to denoise the processed signals.An experiment is finally carried out on PhysioNet database,which verifies the effectiveness of the proposed denoising method.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第4期66-69,共4页
Journal of South China University of Technology(Natural Science Edition)
基金
广东省科技攻关项目(2007B010400049)
粤港关键领域重点突破项目(20090101-1)
关键词
监护信息
小波变换
Hampel滤波
降噪方法
monitoring information
wavelet transform
Hampel filtering
denoising method
