Simulating biological olfactory neural system, KⅢnetwork, which is a high-dimensional chaotic neural network, is designed in this paper. Different from conventional artificial neural network, the KⅢnetwork works in its chaotic trajectory. It can simulate not only the output EEG waveform observed in electrophysiological experiments, but also the biological intelligence for pattern classification. The simulation analysis and application to the recognition of handwriting numerals are presented here. The classification performance of the KⅢnetwork at different noise levels was also investigated. Simulating biological olfactory neural system, KIIInetwork, which is a high-dimensional chaotic neural network, is designed in this paper. Different from conventional artificial neural network, the KIIInetwork works in its chaotic trajectory. It can simulate not only the output EEG waveform observed in electrophysiological experiments, but also the biological intelligence for pattern classification. The simulation analysis and application to the recognition of handwriting numerals are presented here. The classification performance of the KIIInetwork at different noise levels was also investigated.