@inproceedings{f68d690adb574a38a5b1558864f8d1bb,
title = "Almost minimax design of FIR filter using an IRLS algorithm without matrix inversion",
abstract = "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.",
author = "Ruijie Zhao and Zhiping Lin and Toh, {Kar Ann} and Lei Sun and Xiaoping Lai",
year = "2017",
month = jan,
day = "1",
doi = "10.1117/12.2280405",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Guojian Chen and Xudong Jiang and Masayuki Arai",
booktitle = "Second International Workshop on Pattern Recognition",
address = "United States",
note = "2nd International Workshop on Pattern Recognition, IWPR 2017 ; Conference date: 01-05-2017 Through 03-05-2017",
}