Low-Complexity Implementation of the Improved Multiband-Structured Subband Adaptive Filter Algorithm
Low-Complexity Implementation of the Improved Multiband-Structured Subband Adaptive Filter Algorithm
复制标题
DOI：
10.1109/tsp.2015.2450198
复制
发表时间：
2015-06
影响因子：
5.4
通讯作者：
Feiran Yang;Ming Wu;Peifeng Ji;Jun Yang
中科院分区：
文献类型：
--
作者：
Feiran Yang;Ming Wu;Peifeng Ji;Jun Yang
在此之前，我们提出了一种改进的多带结构子带自适应滤波器（IMSAF）算法，以加快MSAF算法的收敛速度。当投影阶数和/或子带的数量增加时，IMSAF算法的收敛速率以增加的复杂度为代价而提高。因此，本文提出了几种方法来降低IMSAF算法的复杂度，无论是在误差向量计算和矩阵求逆运算。具体而言，开发了三种方法来有效地计算误差向量。第一种方法给出了近似滤波，而另外两种方法可以提供快速精确滤波，具有或不具有显式基于递归方案的权向量更新。IMSAF的解相关特性被确定，并且开发了两个简化的变体以降低作为副产品的复杂性，即，简化IMSAF（SIMSAF）和伪IMSAF算法。然后，我们讨论了线性方程组的求解问题。分析和讨论了各种方法的性能优势、局限性和优选应用。在系统辨识的背景下进行计算机模拟，以确定所提出的快速算法的原理和效率。
Previously, we proposed an improved multiband-structured subband adaptive filter (IMSAF) algorithm to accelerate the convergence rate of the MSAF algorithm. When the projection order and/or the number of subbands is increased, the convergence rate of the IMSAF algorithm improves at the cost of increased complexity. Thus, this paper proposes several approaches to reduce the complexity of the IMSAF algorithm, both in error vector calculation and matrix inversion operation. Specifically, three approaches are developed to efficiently calculate error vector. The first approach gives an approximate filtering, whereas the other two approaches can provide a fast exact filtering with or without update of the weight vector explicitly based on a recursive scheme. The decorrelation property of IMSAF is determined, and two simplified variants are developed to reduce the complexity as by-products, i.e., the simplified IMSAF (SIMSAF) and pseudo IMSAF algorithms. Then, we discuss the problem of solving a linear system of equations. The performance advantages, limitations, and preferable applications of various methods are analyzed and discussed. Computer simulations are conducted in the context of system identification to determine the principle and efficiency of the proposed fast algorithms.