A fast algorithm for the high order linear and nonlinear Gaussian regression filter

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

9 Citations (Scopus)

Abstract

In this paper, the general model of the Gaussian regression filter, including both the linear and nonlinear filter of zeroth, second order, has been reviewed. A fast algorithm based on the FFT algorithm has been proposed and tested for its speed and accuracy. Both simulated and practical engineering data have been used in the testing of the proposed algorithm. Results show that with the same accuracy, the processing times of the second order linear and nonlinear regression filters for a typical 40,000 points dataset have been reduced to under 0.5second from the several hours of the traditional convolution algorithm.

LanguageEnglish
Title of host publicationProceedings of the 9th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2009
Publishereuspen
Pages356-359
Number of pages4
Volume2
ISBN (Electronic)9780955308260
Publication statusPublished - 2009
Event9th International Conference of the European Society for Precision Engineering and Nanotechnology - San Sebastian, Spain
Duration: 2 Jun 20095 Jun 2009
Conference number: 9

Conference

Conference9th International Conference of the European Society for Precision Engineering and Nanotechnology
Abbreviated titleEUSPEN 2009
CountrySpain
CitySan Sebastian
Period2/06/095/06/09

Fingerprint

regression analysis
filters
nonlinear filters
linear filters
fast Fourier transformations
Convolution
convolution integrals
Fast Fourier transforms
engineering
Testing
Processing

Cite this

Zeng, W., Jiang, X., Scott, P. J., Xiao, S., & Blunt, L. (2009). A fast algorithm for the high order linear and nonlinear Gaussian regression filter. In Proceedings of the 9th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2009 (Vol. 2, pp. 356-359). euspen.
Zeng, W. ; Jiang, X. ; Scott, P. J. ; Xiao, S. ; Blunt, L. / A fast algorithm for the high order linear and nonlinear Gaussian regression filter. Proceedings of the 9th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2009. Vol. 2 euspen, 2009. pp. 356-359
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Zeng, W, Jiang, X, Scott, PJ, Xiao, S & Blunt, L 2009, A fast algorithm for the high order linear and nonlinear Gaussian regression filter. in Proceedings of the 9th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2009. vol. 2, euspen, pp. 356-359, 9th International Conference of the European Society for Precision Engineering and Nanotechnology, San Sebastian, Spain, 2/06/09.

A fast algorithm for the high order linear and nonlinear Gaussian regression filter. / Zeng, W.; Jiang, X.; Scott, P. J.; Xiao, S.; Blunt, L.

Proceedings of the 9th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2009. Vol. 2 euspen, 2009. p. 356-359.

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

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AB - In this paper, the general model of the Gaussian regression filter, including both the linear and nonlinear filter of zeroth, second order, has been reviewed. A fast algorithm based on the FFT algorithm has been proposed and tested for its speed and accuracy. Both simulated and practical engineering data have been used in the testing of the proposed algorithm. Results show that with the same accuracy, the processing times of the second order linear and nonlinear regression filters for a typical 40,000 points dataset have been reduced to under 0.5second from the several hours of the traditional convolution algorithm.

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Zeng W, Jiang X, Scott PJ, Xiao S, Blunt L. A fast algorithm for the high order linear and nonlinear Gaussian regression filter. In Proceedings of the 9th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2009. Vol. 2. euspen. 2009. p. 356-359