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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationSecond International Workshop on Pattern Recognition
EditorsGuojian Chen, Xudong Jiang, Masayuki Arai
PublisherSPIE
ISBN (Electronic)9781510613508
DOIs
Publication statusPublished - 2017 Jan 1
Event2nd International Workshop on Pattern Recognition, IWPR 2017 - Singapore, Singapore
Duration: 2017 May 12017 May 3

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10443
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

Other2nd International Workshop on Pattern Recognition, IWPR 2017
CountrySingapore
CitySingapore
Period17/5/117/5/3

Fingerprint

FIR Filter
FIR filters
Matrix Inversion
Least Square Algorithm
Minimax
inversions
Filter Design
filters
Weighted Least Squares
Conjugate Gradient Method
conjugate gradient method
Conjugate gradient method
Filtering
Filter
Design
Range of data

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Zhao, R., Lin, Z., Toh, K. A., Sun, L., & Lai, X. (2017). Almost minimax design of FIR filter using an IRLS algorithm without matrix inversion. In G. Chen, X. Jiang, & M. Arai (Eds.), Second International Workshop on Pattern Recognition [104431F] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10443). SPIE. https://doi.org/10.1117/12.2280405
Zhao, Ruijie ; Lin, Zhiping ; Toh, Kar Ann ; Sun, Lei ; Lai, Xiaoping. / Almost minimax design of FIR filter using an IRLS algorithm without matrix inversion. Second International Workshop on Pattern Recognition. editor / Guojian Chen ; Xudong Jiang ; Masayuki Arai. SPIE, 2017. (Proceedings of SPIE - The International Society for Optical Engineering).
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Zhao, R, Lin, Z, Toh, KA, Sun, L & Lai, X 2017, Almost minimax design of FIR filter using an IRLS algorithm without matrix inversion. in G Chen, X Jiang & M Arai (eds), Second International Workshop on Pattern Recognition., 104431F, Proceedings of SPIE - The International Society for Optical Engineering, vol. 10443, SPIE, 2nd International Workshop on Pattern Recognition, IWPR 2017, Singapore, Singapore, 17/5/1. https://doi.org/10.1117/12.2280405

Almost minimax design of FIR filter using an IRLS algorithm without matrix inversion. / Zhao, Ruijie; Lin, Zhiping; Toh, Kar Ann; Sun, Lei; Lai, Xiaoping.

Second International Workshop on Pattern Recognition. ed. / Guojian Chen; Xudong Jiang; Masayuki Arai. SPIE, 2017. 104431F (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10443).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - 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.

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Zhao R, Lin Z, Toh KA, Sun L, Lai X. Almost minimax design of FIR filter using an IRLS algorithm without matrix inversion. In Chen G, Jiang X, Arai M, editors, Second International Workshop on Pattern Recognition. SPIE. 2017. 104431F. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.2280405