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Sigeru Omatu
Osaka Institute of Technology
Hideo Araki
Osaka Institute of Technology
Toru Fujinaka
Hirosima University
Mitsuaki Yano
Osaka Institute of Technology
Michifumi Yoshioka
Osaka Prefecture University
Hiroyuki Nakazumi
Osaka Prefecture Univertisy
Ichiro Tanahashi
Osaka Institute of Technology
Vol. 1 No. 2 (2012), Articles, pages 43-48
Accepted: Jul 1, 2013


Compared with metal oxide semiconductor gas sensors, quarts crystal microbalance (QCM) sensors are sensitive for odors. Using an array of QCM sensors, we measure mixed odors and classify them into an original odor class beforemixing based on neural networks. For simplicity we consider the case that two kinds of odor are mixed since more than two becomes too complex to analyze the classification results. We have used eight sensors and four kinds of odor are used as the original odors. The neural network used here is a conventional layered neural network. The classification is acceptable although the perfect classification could not been achieved.


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