基于多小波噪声方差阈值的信号滤波方法

对信号和噪声的多小波变换进行了研究，根据它们多小波变换下呈现出的截然相反的特征，即随着变换尺度的增大，噪声的变换值迅速减小，而信号的变换值增大，利用相关算法推导并给出了多小波噪声方差阈值的计算公式，基于阈值提出了一种新的多小波信号滤波方法，该方法在噪声方差估计的基础上，对噪声信号变换系数进行处理，减小由噪声产生的系数，同时最大限度地保留有效信号产生的系数，最后由处理后的变换系数进行处理，减少由噪声产生的系数，同时最大限度地保留有效信号产生的系数，最后由处理后的变换系数重构信号，对该方法用典型的GHM双小波进行了仿真分析，结果表明，本文的方法具有很好的滤波效果。

Filtering Algorithm Based on Multiwavelet Noise Variance Threshold

From the contrary characteristics of multiwavelet transforms of signal and noise that the transform values of noises rapidly reduce with the increased transform scale while the transform values of signals rapidly increase, the formula was deduced and presented by correlation algorithm for the multiwavelet noise variance threshold. Based on the threshold, a new filtering algorithm with multiwavelet was proposed. On the basis of an estimated noise variance, the algorthm processes the transformed coefficients by weakening the coefficients produced by a noise while keeping the coefficient produced by a signal as much as possible. The signal is reconstructed by the processed coefficients. The simulation made with the algorithm using the classic GHM multiwavelet indicates that the proposed algorithm has a good filtering effect.