基于小波平滑的超高斯与亚高斯信号盲源分离算法
Blind Source Separation Algorithm Based on Wavelet Smoothing for Super-Gaussian and Sub-Gaussian Signals
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摘要: 为了分离超高斯与亚高斯信号，利用小波变换的高低频系数作为平滑因子，建立以分母作为预测误差的信噪比目标函数，优化目标函数以求解分离矩阵．仿真表明，该算法能够有效地分离出源信号．Abstract: In order to separate super-Gaussian and sub-Gaussian signals,this paper uses high-and low-frequency coefficients of wavelet transform as smooth factors,then builds a signal-to-noise ratio objective function,which uses the denominator as prediction error and can be optimized to resolve separable matrix.Simulation shows that this algorithm can separate source signals effectively.
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