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

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

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 matri...

Full description

Saved in:
Bibliographic Details
Main Authors: Zhao, Ruijie, Lin, Zhiping, Toh, Kar-Ann, Sun, Lei, Lai, Xiaoping
Other Authors: Jiang, Xudong
Format: Conference or Workshop Item
Language:English
Published: 2018
Subjects:
FIR Filter
DRNTU::Science::Biological sciences
Conjugate Gradient Method
Online Access:https://hdl.handle.net/10356/102533
http://hdl.handle.net/10220/47263
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
Description
Summary: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.

Similar Items