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

机译:FIR滤波器设计的一种新的迭代重新超强最小二乘算法

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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,迭代重复最小二乘(IRLS)算法是用于数字滤波器的设计的有效技术。 IRLS算法中的主要计算负载是求解一系列加权最小二乘(WLS)子问题,这通常需要耗时的矩阵反转评估。本文提出了一种新的和非常有效的IRLS算法,其中开发了一个简单的迭代程序,用于解决这些WLS子问题。验证了迭代程序保证收敛,并且是比使用矩阵反转更有效的。因此,设计效率大大提高,特别是对于高阶滤波器。对某些现有算法的设计示例和比较显示了所提出的算法的优异性能。

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