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A new iterative reweighted least squares algorithm for the design of FIR filters

机译:用于FIR滤波器设计的新的迭代加权最小二乘算法

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It is known that iterative reweighted least squares (IRLS) algorithms are efficient techniques for the design of digital filters. The main computational load in IRLS algorithms is to solve a series of weighted least squares (WLS) subproblems, which usually needs the time-consuming evaluation of matrix inversion. This paper presents a new and very efficient IRLS algorithm, in which a simple iterative procedure is developed for solving those WLS subproblems. It is verified that the iterative procedure is guaranteed to converge and is computationally more efficient than using matrix inversion. Thus, the design efficiency is improved greatly, especially for high-order filters. Design examples and comparisons to some existing algorithms are given to show the excellent performance of the proposed algorithm.
机译:众所周知,迭代加权最小二乘(IRLS)算法是设计数字滤波器的有效技术。 IRLS算法的主要计算负担是解决一系列加权最小二乘(WLS)子问题,这通常需要耗时的矩阵求逆评估。本文提出了一种新的,非常有效的IRLS算法,其中开发了一种简单的迭代程序来解决这些WLS子问题。验证了迭代过程可以收敛,并且在计算上比使用矩阵求逆更为有效。因此,大大提高了设计效率,特别是对于高阶滤波器。给出了设计实例并与一些现有算法进行了比较,以显示该算法的出色性能。

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