Axioms 2013, 2(1), 44-57; doi:10.3390/axioms2010044
Article

Signal Estimation Using Wavelet Analysis of Solution Monitoring Data for Nuclear Safeguards

Statistical Sciences, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
* Author to whom correspondence should be addressed.
Received: 31 January 2013; in revised form: 4 March 2013 / Accepted: 7 March 2013 / Published: 20 March 2013
(This article belongs to the Special Issue Wavelets and Applications)
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Abstract: Wavelets are explored as a data smoothing (or de-noising) option for solution monitoring data in nuclear safeguards. In wavelet-smoothed data, the Gibbs phenomenon can obscure important data features that may be of interest. This paper compares wavelet smoothing to piecewise linear smoothing and local kernel smoothing, and illustrates that the Haar wavelet basis is effective for reducing the Gibbs phenomenon.
Keywords: wavelet smoothing; wavelet de-noising; Gibbs phenomenon

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MDPI and ACS Style

Burr, T.; Longo, C. Signal Estimation Using Wavelet Analysis of Solution Monitoring Data for Nuclear Safeguards. Axioms 2013, 2, 44-57.

AMA Style

Burr T, Longo C. Signal Estimation Using Wavelet Analysis of Solution Monitoring Data for Nuclear Safeguards. Axioms. 2013; 2(1):44-57.

Chicago/Turabian Style

Burr, Tom; Longo, Claire. 2013. "Signal Estimation Using Wavelet Analysis of Solution Monitoring Data for Nuclear Safeguards." Axioms 2, no. 1: 44-57.

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