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

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

doi:10.1117/12.2280405

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

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

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Second International Workshop on Pattern Recognition
Editors	Guojian Chen, Xudong Jiang, Masayuki Arai
Publisher	SPIE
ISBN (Electronic)	9781510613508
DOIs	https://doi.org/10.1117/12.2280405
Publication status	Published - 2017
Event	2nd International Workshop on Pattern Recognition, IWPR 2017 - Singapore, Singapore Duration: 2017 May 1 → 2017 May 3

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	10443
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Other

Other	2nd International Workshop on Pattern Recognition, IWPR 2017
Country/Territory	Singapore
City	Singapore
Period	17/5/1 → 17/5/3

Bibliographical note

Funding Information:
This research was supported partially by the National Nature Science Foundation of China under Grants 61304142, 61573123 and 61673059, and partially by the Singapore Academic Research Fund (AcRF) Tier 1 under Project RG 31/16.

Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

All Science Journal Classification (ASJC) codes

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

Access to Document

10.1117/12.2280405

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

@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",

note = "Funding Information: This research was supported partially by the National Nature Science Foundation of China under Grants 61304142, 61573123 and 61673059, and partially by the Singapore Academic Research Fund (AcRF) Tier 1 under Project RG 31/16. Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; 2nd International Workshop on Pattern Recognition, IWPR 2017 ; Conference date: 01-05-2017 Through 03-05-2017",

year = "2017",

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",

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address = "United States",

}

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 et al.

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 proceeding › Conference contribution

TY - GEN

T1 - Almost minimax design of FIR filter using an IRLS algorithm without matrix inversion

AU - Zhao, Ruijie

AU - Lin, Zhiping

AU - Toh, Kar Ann

AU - Sun, Lei

AU - Lai, Xiaoping

N1 - Funding Information: This research was supported partially by the National Nature Science Foundation of China under Grants 61304142, 61573123 and 61673059, and partially by the Singapore Academic Research Fund (AcRF) Tier 1 under Project RG 31/16. Publisher Copyright: © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

PY - 2017

Y1 - 2017

N2 - 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.

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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T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Second International Workshop on Pattern Recognition

A2 - Chen, Guojian

A2 - Jiang, Xudong

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PB - SPIE

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Y2 - 1 May 2017 through 3 May 2017

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

Abstract

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