基于小波包-变分贝叶斯独立分量分析的源信号盲分离方法

The Blind Source Separation Method Based on Wavelet Packet and Variational Bayes Independent Compoment Analysis

结合小波包分析和变分贝叶斯独立分量分析的各自优点,提出了一种基于小波包-变分贝叶斯独立分量分析的盲源分离方法,该方法利用小波包对观测信号进行分解,将得到的重构的小波包系数组成新的观测信号,再利用变分贝叶斯推论对源信号进行估计。仿真结果表明,该方法是有效的,即使在非常低的信噪比噪声混合下,也能得到非常满意的分离效果。

Combined with the respective advantages of wavelet packet analysis and variational Bayesian independent component analysis （VBICA） ,a blind source separation method based on wavelet packet and VBICA is proposed. The observation signals are decomposed by the wavelet packet and the obtained reconstruct wavelet packet coefficients constitute the new observation signals. The source signals are estimated by the VBICA method. The simulation results show that the proposed method is very effective. Even under noisy mixture at the very low signal -to -noise ratio, the satisfactory separation performance can be also obtained.