欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
为了更好地消除混杂在表面肌电信号（s EMG）中的噪声,提出一种基于噪声统计特性的EMD自相关消噪方法。首先,对含噪s EMG信号进行EMD分解,并根据噪声统计特性降低低信噪比的高频IMF分量的能量后重组信号。其次,对重组后的信号进行自相关函数特性的EMD分解,并对自相关函数方差低于阈值的高频IMF分量进行小波去噪。最后,把处理后的高频IMF分量和低频IMF分量重构,得到的信号即为消噪信号。实验结果表明,该方法不仅能更好的消除噪声,而且在低信噪比情况下有良好表现。
英文摘要：
A de-nosing method based on the noise statistical EMD autocorrelation is proposed to eliminate the noise mixed with s EMG. Firstly, the s EMG signals are recombined through EMD based on energy reduction of low SNR high-frequency IMF according to the noise statistics. Then, the recombined signals are decomposed by EMD, and high-frequency IMFs whose autocorrelation function variance is below the threshold are denoised by the wavelet. Finally, the processed high-frequency IMF and low-frequency IMF are reconstructed to get the signal denoised. The experimental results show that the method not only can well eliminate noise, but also a good performance is achieved under the condition of low signal-to-noise ratio.
同期刊论文项目
同项目期刊论文
期刊信息
位置：