论文标题
矩阵自适应合成过滤器用于均匀滤波器库
Matrix Adaptive Synthesis Filter for Uniform Filter Bank
论文作者
论文摘要
在本文中，我们使用矩阵自适应过滤器作为均匀过滤器库（UFB）的合成阶段来重建输入信号。我们首先通过在UFB的合成阶段应用最佳滤波模型并获得矩阵Wiener滤波器的表达式来开发其背后的数学理论。我们已经开发了一个定理，我们使用该定理来进一步简化表达式。在没有有关分析阶段的必需信息的情况下，我们使用自适应过滤来得出Wiener解决方案。我们使用最小平方（LMS）算法来更新过滤器系数。通过实验结果，我们发现自适应过滤器是稳定的维纳滤波器的收敛性。
In this paper, we use a matrix adaptive filter as the synthesis stage of a Uniform Filter Bank (UFB) to reconstruct the input signal. We first develop the mathematical theory behind it by applying the model of optimal filtering at the synthesis stage of the UFB and obtaining an expression for the matrix Wiener filter. We have developed a theorem which we use to simplify the expression further. In the absence of required information about the analysis stage, we use adaptive filtering to arrive at the Wiener solution. We use the Least Mean Square (LMS) algorithm to update the filter coefficients. Through experimental results, we find that the adaptive filter is convergent for a stable Wiener filter.
