Classifier comparison and sensor selection for e-noses

M. Pardo, G. Sberveglieri, B. Sisk, N. Lewis

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)


Data derived from chemical vapor sensor arrays was analyzed using Fischer linear discriminant analysis (LDA) and multilayer perceptrons (MLP). Datasets produced by an e-nose based on polymer-carbon black sensors and those produced by a second e-nose based on five thin film metal oxide sensors was analyzed. The datasets were chosen to give classification problems of varying hardness: from the discrimination of two almost Gaussian distributed analytes to the discrimination of two analytes in the presents of interferents at different concentration levels. The performance of the best 5-sensors subset selected with MLP was found to be better than the performance of the LDA-selected subsets.

Original languageEnglish
Number of pages5
Publication statusPublished - Dec 1 2003
EventSecond International Conference on Sensors: IEEE Sensors 2003 - Toronto, Ont., Canada
Duration: Oct 22 2003Oct 24 2003


OtherSecond International Conference on Sensors: IEEE Sensors 2003
CityToronto, Ont.

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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