利用直接矩阵求逆和临界采样子带自适应滤波器的快速系统辨识

Fast System Identification Using Direct Matrix Inversion and a Critically Sampled Subband Adaptive Filter

在许多应用中,子带自适应滤波器结构已经显示了其在计算和性能上的优点。基于最近提出的一个采用临界采样滤波器组的子带自适应结构,该文引入了子带直接矩阵求逆(DMI)算法。在保持了该算法快速收敛优点的同时,利用相关矩阵块三对角的特殊结构,降低了该算法的计算复杂度。理论分析及计算机实验显示,子带直接矩阵求逆算法只需经过较少的更新次数——自适应子滤波器自由度的两倍,就能够收敛到高于最小均方误差的3dB附近。

In many applications subband adaptive filter structures have been shown to be superior computationally and performancewise. This paper presents a subband Direct Matrix Inversion （DMI） algorithm suitable for use within a recently proposed adaptive filter structure employing critically sampled filter banks. This new method reduces the computational complexity by using the block tridiagonal structure of the input sample correlation matrix, and at the same time keeps the advantage of fast convergence. Experimental results show that the output residue power of the subband DMI algorithm is around 3dB upon the optimum value after only 2K updating of the adaptive subfilters, where K is the dimension of the adaptive subfilters.