Statistical model for noisy data selection

Wieslaw Kicinski

doi:10.1117/12.609586

23 May 2005 Statistical model for noisy data selection

Wieslaw Kicinski

Proceedings Volume 5846, Noise and Information in Nanoelectronics, Sensors, and Standards III; (2005) https://doi.org/10.1117/12.609586
Event: SPIE Third International Symposium on Fluctuations and Noise, 2005, Austin, Texas, United States

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.

Citation Download Citation

Wieslaw Kicinski "Statistical model for noisy data selection", Proc. SPIE 5846, Noise and Information in Nanoelectronics, Sensors, and Standards III, (23 May 2005); https://doi.org/10.1117/12.609586

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