Network Model Of Olfactory Neural System Research And Application

According to the entire neural architecture of olfactory system, and lots of electro-psychological experiment, K set model is designed. Among them KIII model is a high-dimensional chaotic neural network, which cannot only simulate the EEG waveform observed in experiments, but also the biological intelligence for pattern classification. It also provides a novel explanation of the signal processing mechanism of the neural system in the aspect of nonlinear dynamics.The numeral analysis of the K set model, including KO, KI, KII and KIII model, is presented in this thesis. From the analysis result, it can be seen that KIII network can well simulate the biological olfactory neural system. Different from conventional artificial neural network, the KIII network works in its chaotic trajectory. The learning and pattern recognition process of the network is also relative to its memory basins, which are some kind of chaotic attractors.Based on the understanding of the K set model and previous work, the KIII model is applied on image pattern recognition and handwriting numerals recognition. The performance of the KIII network is also compared with those results when using conventional artificial neural networks. The pattern recognition results prove that the KIII network is a good pattern classifier.