Abstract
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 language | English |
|---|---|
| Pages | 606-610 |
| Number of pages | 5 |
| Publication status | Published - Dec 1 2003 |
| Event | Second International Conference on Sensors: IEEE Sensors 2003 - Toronto, Ont., Canada Duration: Oct 22 2003 → Oct 24 2003 |
Other
| Other | Second International Conference on Sensors: IEEE Sensors 2003 |
|---|---|
| Country | Canada |
| City | Toronto, Ont. |
| Period | 10/22/03 → 10/24/03 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering
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Cite this
Pardo, M., Sberveglieri, G., Sisk, B., & Lewis, N. (2003). Classifier comparison and sensor selection for e-noses. 606-610. Paper presented at Second International Conference on Sensors: IEEE Sensors 2003, Toronto, Ont., Canada.