A new linguistic fuzzy approach to recognition of olfactory signals

In this paper we propose a new fuzzy linguistic method to recognize odorant samples. The method is applied to raw experimental data collected from a sensor array that comprises sixteen conducting polymer sensors with partially overlapping sensitivities. The sensors are exposed to odor samples and the percentage change in resistance is used for classification. The method describes the shape of each sensor response in terms of linguistic expressions derived from a fuzzy partition of the area occupied by the response. A purposely-defined weighted distance is used to compare the linguistic descriptions. Results on the application of the method to the classification of three chemicals in two different concentrations are presented.