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Proceedings Paper

Statistical model for noisy data selection
Author(s): Wieslaw Kicinski
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Paper Abstract

In this paper a statistical model for noisy data selection has been presented. It combines two powerful tools: a local wavelet analysis and multidimensional data analysis of wavelet transform coefficients. In the proposed model the adapted Malvar wavelet transform has been applied. It leads to a partition of the measuring signal to isolate transients. The multidimensional wavelet coefficients analysis has been applied to constitute a set of discriminating parameters that can be used to explore features characterizing transients caused by the air bubbles from diver's oxygen tanks.

Paper Details

Date Published: 23 May 2005
PDF: 7 pages
Proc. SPIE 5846, Noise and Information in Nanoelectronics, Sensors, and Standards III, (23 May 2005); doi: 10.1117/12.609586
Show Author Affiliations
Wieslaw Kicinski, Naval Univ. of Gdynia (Poland)


Published in SPIE Proceedings Vol. 5846:
Noise and Information in Nanoelectronics, Sensors, and Standards III
Janos A. Bergou; Janusz M. Smulko; Mark I. Dykman; Lijun Wang, Editor(s)

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