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Concentration estimation of gas mixtures using a tin oxide gas sensor and fuzzy ART  

Lee Jeong-Hun (School of Electrical Engineering and Computer Science, Kyungpook National University)
Cho Jung-Hwan (School of Electrical Engineering and Computer Science, Kyungpook National University)
Jeon Gi-Joon (School of Electrical Engineering and Computer Science, Kyungpook National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SC / v.43, no.4, 2006 , pp. 21-29 More about this Journal
Abstract
A fuzzy ARTMAP neural network and a fuzzy ART neural network are proposed to identify $H_2S,\;NH_3$, and their mixtures and to estimate their concentrations, respectively. Features are extracted from a tin oxide gas sensor operated in a thermal modulation plan. After dimensions of the features are reduced by a preprocessing scheme, the features are fed into the proposed fuzzy neural networks. By computer simulations, the proposed method is shown to be fast in learning and stable in concentration estimating compared with other methods.
Keywords
fuzzy ARTMAP; fuzzy ART; gas mixture; concentration estimation;
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