Abstract. Based on the research on mechanism of biological olfactory system, we constructed a K-set, which is a novel bionic neural network. Founded on the groundwork of K0, KI and KII sets, the KIII set in the K-set hierarchy simulates the whole olfactory neural system. In contrast to the conventional artificial neural networks, the KIII set operates in nonconvergent 'chaotic' dynamical modes similar to the biological olfactory system. In this paper, an application of electronic nose-brain for tea classification using the KIII set is presented and its performance is evaluated in comparison with other methods.
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.
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