摘要
研究了心冲击图的正交小波变换最小均方自适应去噪;阐述了基于正交小波变换的最小均方自适应去噪原理;利用径向高斯核函数对心冲击图进行自适应时频联合分析,得到了中心频率并确定了小波分解尺度;提出了通过选择小波基函数和输入信号长度确定自适应滤波器阶数的方法;从矩阵角度给出了算法的实现步骤,并分析了正交小波变换提高最小均方算法收敛速度的原因。实验结果表明,正交小波变换最小均方算法使自适应去噪后的心冲击图更快达到稳态,随心动周期的变化趋势更加明显。比较去噪前后心冲击图的功率谱密度可知,正交小波变换最小均方算法在保留心冲击图特征的同时自适应地去除了其中的时变噪声,获得了良好的去噪效果。
The ballistocardiogram least mean square adaptive de-noising method based on orthogonal wavelet transform was researched. The principal of least mean square adaptive de-noising method based on orthogonal wavelet transform was analyzed. The decomposition scale was confirmed by central frequency of ballistocardiogram gained from joint time- frequency analysis based on adaptive radial gauss kernel function, and the level confirmed approach for adaptive filter was proposed by choosing and choosing the wavelet base and the length of input signal. The realization approach was described from the view of matrix, and the reason why orthogonal wavelet transform could improve convergence speed of least mean square algorithm was explained. The experiment results show that, by using least mean square adaptive de-noising method based on orthogonal wavelet transform, the adaptive denoised ballistocardiogram becomes steady more quickly and its wave changing along with cardiac cycle is clearer. Compared with power spectrum density of before and after denoised signal, least mean square adaptive de-noising method based on orthogonal wavelet transform holds the characters of ballistocardiogram while denoising time variable noise,and gains better denoising results.
出处
《计算机科学》
CSCD
北大核心
2010年第8期232-235,共4页
Computer Science
基金
国家自然科学基金项目(50477015)资助
关键词
心冲击图
正交小波变换
时频联合分析
最小均方
自适应去噪
Ballistocardiogram, Orthogonal wavelet transform, Joint time-frequency analysis, Least mean square, Adap-tive denoising
