标题：Almost Minimax Design of FIR filter Using an IRLS Algorithm without Matrix Inversion
作者：Zhao, Rujie; Lin, Zhiping; Toh, Kar-Ann; Sun, Lei; Lai, Xiaoping
作者机构：[Zhao, Rujie] Shandong Univ, Sch Mech Elect & Informat Engn, Weihai 264209, Peoples R China.; [Zhao, Rujie; Lin, Zhiping] Nanyang Technol Univ, Sch 更多
会议名称：2nd International Workshop on Pattern Recognition
会议日期：MAY 01-03, 2017
来源：SECOND INTERNATIONAL WORKSHOP ON PATTERN RECOGNITION
关键词：Conjugate gradient method; FIR filters; IRLS algorithm; Minimax design
摘要：An iterative reweighted least squares (IRLS) algorithm is presented in this paper for the minimax design of FIR filters. In the algorithm, the resulted subproblems generated by the weighted least squares (WLS) are solved by using the conjugate gradient (CG) method instead of the time-consuming matrix inversion method. An almost minimax solution for filter design is consequently obtained. This solution is found to be very efficient compared with most existing algorithms. Moreover, the filtering solution is flexible enough for extension towards a broad range of filter designs, including constrained filters. Two design examples are given and the comparison with other existing algorithms shows the excellent performance of the proposed algorithm.