Almost minimax design of FIR filter using an IRLS algorithm without matrix inversion
Date of Issue2017
Second International Workshop on Pattern Recognition
School of Electrical and Electronic Engineering
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.
Conjugate Gradient Method
© 2017 Society of Photo-optical Instrumentation Engineers (SPIE). This paper was published in Second International Workshop on Pattern Recognition and is made available as an electronic reprint (preprint) with permission of Society of Photo-optical Instrumentation Engineers (SPIE). The published version is available at: [http://dx.doi.org/10.1117/12.2280405]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.