A neuro-fuzzy model applied to odor recognition in an artificial nose

Authors:
Cleber Zanchettin;Teresa B. Ludermir
Affiliations:
Center of Informatics - Federal University of Pernambuco, P. O. Box 7851, Cidade Universitária, Recife - PE, Brazil;Center of Informatics - Federal University of Pernambuco, P. O. Box 7851, Cidade Universitária, Recife - PE, Brazil
Venue:
Design and application of hybrid intelligent systems
Year:
2003

Citing 4
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Abstract

This work presents an application of a neuro-fuzzy model as a pattern recognition system for an artificial nose. The proposed model seeks to select important features among given plausible features while maintaining maximum recognition rate. The knowledge acquired by the network can be described as a set of interpretable rules. The results of neuro-fuzzy model are compared with two other widely used models of odor pattern classification, the Multi-Layer Perceptron (MLP) neural network and the Time Delay Neural Network (TDNN), in the analysis of signals generated by eight conducting polymer sensors exposed to gases derived from the petroliferous industry.