Almost minimax design of FIR filter using an IRLS algorithm without matrix inversion

Ruijie Zhao, Zhiping Lin*, Kar Ann Toh, Lei Sun, Xiaoping Lai

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

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.

源语言英语
主期刊名Second International Workshop on Pattern Recognition
编辑Guojian Chen, Xudong Jiang, Masayuki Arai
出版商SPIE
ISBN(电子版)9781510613508
DOI
出版状态已出版 - 2017
活动2nd International Workshop on Pattern Recognition, IWPR 2017 - Singapore, 新加坡
期限: 1 5月 20173 5月 2017

出版系列

姓名Proceedings of SPIE - The International Society for Optical Engineering
10443
ISSN(印刷版)0277-786X
ISSN(电子版)1996-756X

会议

会议2nd International Workshop on Pattern Recognition, IWPR 2017
国家/地区新加坡
Singapore
时期1/05/173/05/17

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