Application of nonlinearity measures to chemical sensor signals Conference Paper uri icon


  • 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.

name of conference

  • Noise and Information in Nanoelectronics, Sensors, and Standards

published proceedings


author list (cited authors)

  • Smulko, J. M., Kish, L. B., & Schmera, G.

citation count

  • 5

complete list of authors

  • Smulko, JM||Kish, LB||Schmera, G

editor list (cited editors)

  • Kish, L. B., Green, F., Iannaccone, G., & Vig, J. R.

publication date

  • January 2003