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Progress in bionic information processing techniques for an electronic nose based on olfactory models
Authors:Guang Li  Jun Fu  Jia Zhang  JunBao Zheng
Institution:(1) State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, 310027, China;(2) Department of Biomedical Engineering, Zhejiang University, Hangzhou, 310027, China;(3) Sir Run Run Shaw Hospital, Affiliated with the School of Medicine, Zhejiang University, Hangzhou, 310016, China;(4) Faculty of Informatics and Electronics, Zhejiang Sci-Tech University, Hangzhou, 310018, China
Abstract:As a novel bionic analytical technique, an electronic nose, inspired by the mechanism of the biological olfactory system and integrated with modern sensing technology, electronic technology and pattern recognition technology, has been widely used in many areas. Moreover, recent basic research findings in biological olfaction combined with computational neuroscience promote its development both in methodology and application. In this review, the basic information processing principle of biological olfaction and artificial olfaction are summarized and compared, and four olfactory models and their applications to electronic noses are presented. Finally, a chaotic olfactory neural network is detailed and the utilization of several biologically oriented learning rules and its spatiotemporal dynamic propties for electronic noses are discussed. The integration of various phenomena and their mechanisms for biological olfaction into an electronic nose context for information processing will not only make them more bionic, but also perform better than conventional methods. However, many problems still remain, which should be solved by further cooperation between theorists and engineers. Supported by the National Creative Research Groups Science Foundation of China (Grant No. 60421002) and National Basic Research Programme of China (Grant No. 2004CB720302)
Keywords:artificial olfaction  olfactory model  pattern recognition  electronic nose  bionics
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