摘要
针对多通道表面肌电信号(SEMG)采集时形成的混迭现象,提出一种基于时频分析的参考累积量盲源分离方法。以多路观测信号互为参照分别计算累积量矩阵,利用时频分析得到时间尺度累积量矩阵,并构造对照函数,通过非正交联合对角化方法得到SEMG的最优估计。仿真实验表明该算法在解决SEMG的混迭现象有很好的分离效果,与FastICA、JADE算法相比,信号间的相似系数和算法性能指数明显改善,算法效率提高。
In order to eliminate the signal aliasing of multi-channel Surface Electromyography （SEMG）,this paper proposes a new separation method based on the referenced cumulant on the time-frequency. First, the technique calculates the cumulant matrices through taking the observation signals as the cross-reference signals. ;second, gets the time-scale cumulant matrices through the time-frequency analysis; third, constructs the contrast function by the time-scale cumulant matrices. The estimation of the SEMG can be performed by the non-orthogonal joint diagonalization. The experimental results indicate that this method is an effective way to separate multi-channel SEMG, its separating effect is better than the FastICA and the JADE from the coefficient of similarity and the Performance Index, and the efficiency of this algorithm is also improved.
出处
《传感技术学报》
CAS
CSCD
北大核心
2009年第8期1204-1207,共4页
Chinese Journal of Sensors and Actuators
基金
国家863项目资助(2008AA04Z212)
国家自然科学基金资助(60874102)
关键词
表面肌电信号
盲源分离
参考累积量矩阵
非正交联合对角化
Surface Electromyography
Blind Source Separation
Referenced Cumulant Matrices
Non-Orthogonal Joint Diagonalization
