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Proceedings Paper

Application of nonlinearity measures to chemical sensor signals
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Paper Abstract

The stochastic component of chemical sensor signal contains valuable information that can be visualized not only by spectral analysis but also by using nonlinear characteristic components. The analysis of nonlinear stochastic components enables the extraction of physically interesting and useful features and may lead to significant improvements in selectivity and sensitivity. Various measures of nonlinearity are presented and estimated for sample sensor data obtained from commercial chemical sensors. Particular attention was paid to the bispectrum function that detects nonlinear and non-stationary components in the analyzed noise. The results suggest that bispectrum measurements provide valuable information about the nature of noise generation in chemical sensors. Moreover, we have found, by analyzing skewness and kurtosis distributions, that the measured time series were stationary.

Paper Details

Date Published: 8 May 2003
PDF: 9 pages
Proc. SPIE 5115, Noise and Information in Nanoelectronics, Sensors, and Standards, (8 May 2003); doi: 10.1117/12.499779
Show Author Affiliations
Janusz M. Smulko, Dept. of Electrical Engineering, Texas A&M Univ. (United States)
Gdansk Univ. of Technology (Poland)
Laszlo B. Kish, Dept. of Electrical Engineering, Texas A&M Univ. (United States)
Gabor Schmera, Space and Naval Warfare Systems Ctr., San Diego (United States)


Published in SPIE Proceedings Vol. 5115:
Noise and Information in Nanoelectronics, Sensors, and Standards
Laszlo B. Kish; Frederick Green; Giuseppe Iannaccone; John R. Vig, Editor(s)

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