NDLI: Confidence interval estimation using polynomial chaos theory

Content Provider	IEEE Xplore Digital Library
Author	Smith, A. Monti, A. Ponci, F.
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. Eng., Univ. of South Carolina, Columbia, SC (Smith, A.; Monti, A.; Ponci, F.)
Abstract	This paper proposes an analytical method to estimate the confidence interval of a measurement using polynomial chaos theory (PCT). In previous work, the authors proposed an approach based on polynomial chaos theory (PCT) to evaluate the worst-case in an indirect measurement process, which in some cases can be considered as 100% confidence interval estimate. In many practical cases though, it is important to be able to determine the confidence intervals. The confidence interval computed as the integral the probability density function (PDF), the cumulative distribution function (CDF), requires the availability of the PDF. An analytical approach to calculate of the PDF associated to a PCT polynomial has been previously proposed in literature. This analytical approach based on a regularized estimation of the joint PDF, yields a well-defined and well shaped PDF. The method proposed in this paper is based on the analytical reconstruction of PDF from the polynomial structure of the PCT expansion. Once the PDF is obtained, the integral can be calculated and an estimation of the confidence interval can be derived. This methodology is demonstrated using an indirect loop impedance measurement as an example.
Starting Page	12
Ending Page	16
File Size	524188
Page Count	5
File Format	PDF
ISBN	9781424422364
DOI	10.1109/AMUEM.2008.4589927
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-21
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Chaos Uncertainty Artificial neural networks Probability density function Polynomials Random variables electric variables measurement uncertainty Equations
Content Type	Text
Resource Type	Article

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