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Design and Implementation of a Noise Tolerant Polynomial Nonlinear ARX Model using the Averaging Wavelet Method

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International Journal of Computer Applications
© 2011 by IJCA Journal
Volume 35 - Number 1
Year of Publication: 2011
Authors:
Ehsan Khadem Olama
Hooshang Jazayeri-Rad
10.5120/4362-6012

Ehsan Khadem Olama and Hooshang Jazayeri-Rad. Article: Design and Implementation of a Noise Tolerant Polynomial Nonlinear ARX Model using the Averaging Wavelet Method. International Journal of Computer Applications 35(1):1-5, December 2011. Full text available. BibTeX

@article{key:article,
	author = {Ehsan Khadem Olama and Hooshang Jazayeri-Rad},
	title = {Article: Design and Implementation of a Noise Tolerant Polynomial Nonlinear ARX Model using the Averaging Wavelet Method},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {35},
	number = {1},
	pages = {1-5},
	month = {December},
	note = {Full text available}
}

Abstract

In this paper, a new nonlinear wavelet identification structure is proposed for high noise resistive soft sensors. This method uses proposed Polynomial Nonlinear Auto Regressive Exogenous Model, which can be solved with linear Gaussian Least Square Method, alongside the Averaging Wavelet Method (AWM) filter. AWM uses the approximation spaces for analyzing the signals and reduce the noise by a mean filtering over sub-resolutions. Conventional wavelet modeling methods use the detail spaces of the decomposed signal for signal modeling. The application results show that this method can be more accurate in high level noisy environments than the conventional wavelet modeling methods can tolerate.

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