Abstract
The Lorentzian model is an analytic expression that describes the time response of electronic nose sensors. We show how this model can be utilized to calculate a normalized similarity index between any two measurements. The set of similarity indices is then used for two purposes: visualization of the data, and classification of new samples. The visualization is carried out using graph drawing tools, and the results are shown to bear some desired properties. The classification is done using a majority-decision type algorithm, and is demonstrated to have very low error rate.
Original language | American English |
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Title of host publication | Proceedings of the 9th International Symposium on Olfaction and Electronic Nose ISOEN '02 |
Place of Publication | Rome |
Publisher | Aracne Editrice |
Pages | 141-146 |
Number of pages | 6 |
State | Published - 2003 |
Keywords
- electronic noses
- similarity index
- feature extraction
- Lorentzian model
- graph drawing
- Visualization
- classification