This paper presents a novel neural network called KIII model for pattern recognition in artificial olfaction, whose topological structure and parameters are based on anatomical and electrophysiology experiments in mammalian olfactory system. Six data sets of three volatile organic compounds in different conditions, each with a wide range of concentrations, are obtained by a signal acquisition system with tin oxide gas sensor array. They are input into KIII model for training and test. Experimental results show that the system had a good classification performance in a wide concentration range while only a few training samples needed.
Application of biologically modeled chaotic neural network to pattern recognition in artificial olfaction. Publishing Authors By Initials
Application of biologically modeled chaotic neural network to pattern recognition in artificial olfaction. Journal Published:
PUBLICATION TYPE: Journal Article
Journal: Conference proceedings : ... Annual International
VOLUME: 5
Page Numbers: 4666-9
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ISSN: 1557-170X
DAY: 6
MONTH: 02
YEAR: 2005
Application of biologically modeled chaotic neural network to pattern recognition in artificial olfaction. Information
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LANGUAGE: eng
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Grant and Affiliation Information for Application of biologically modeled chaotic neural network to pattern recognition in artificial olfaction.
AFFILIATION: Department of Biomedical Engineering, Zhejiang University, Hangzhou, 310027, China.
Country: United States
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MEDLINETA: Conf Proc IEEE Eng Med Biol So
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