Search:
Computing and Library Services - delivering an inspiring information environment

A Fast Algorithm for the High Order Linear and Nonlinear Gaussian Regression filter

Zeng, Wenhan, Jiang, Xiang, Scott, Paul J., Xiao, Shaojun and Blunt, Liam (2009) A Fast Algorithm for the High Order Linear and Nonlinear Gaussian Regression filter. In: Proceedings of the 9 th international conference of the european society for precision engineering and nanotechnology. euspen, San Sebastian, Spain, pp. 356-359. ISBN 978-0-9553082-6-0

[img] PDF
P7.51_Zeng.pdf - Published Version

Download (68kB)

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.

Item Type: Book Chapter
Contributors:
ContributionNameEmail
CompilerNyman, D.UNSPECIFIED
Subjects: T Technology > TS Manufactures
Schools: School of Computing and Engineering
School of Computing and Engineering > Centre for Precision Technologies
School of Computing and Engineering > Centre for Precision Technologies > Surface Metrology Group
Related URLs:
Depositing User: Wenhan Zeng
Date Deposited: 27 Apr 2009 11:17
Last Modified: 21 Nov 2013 14:05
URI: http://eprints.hud.ac.uk/id/eprint/3980

Downloads

Downloads per month over past year

Repository Staff Only: item control page

View Item View Item

University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©