Theory And Application Of Artificial Olfactory Information Processing Study

The artificial olfactory system based on gas sensitive sensors array and patterns recognition technology is an important method to recognize gases use the cross sensitivity of gas sensitive sensor. Main study of this paper is classification methods of patterns recognition of artificial olfactory system. Blind source separation is discussed also in this paper, and the thought of using blind source separation in artificial olfactory information processing is proposed.Firstly, the simple history and the research status is summarized in this paper. Then different classification methods of patterns recognition of artificial olfactory system are introduced and their advantages and disadvantages are compared.Later, an artificial olfactory system made by ourselves is introduces and is used to recognize different gases with neural network patterns recognition method. The algorithm of SOM neural network is improved for better system's performance. A forgetting factor is used in algorithm in order to accelerate its convergence speed.Finally, blind source separation is researched. The thought of applying blind source separation to artificial olfactory information processing is proposed, it provides a new method for artificial olfactory information processing. An advance algorithm of fast independent component analysis based on blind source separation is proposed and simulated on computer.