Application of novel chaotic neural networks to text classification based on PCA

Authors:
Jin Zhang;Guang Li;Walter J. Freeman
Affiliations:
Department of Biomedical Engineering, Zhejiang University, Hangzhou, China;National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China;Division of Neurobiology, University of California at Berkeley, Berkeley, CA
Venue:
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Year:
2006

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Abstract

To model mammalian olfactory neural systems, a chaotic neural network entitled K-set has been constructed. This neural network with non-convergent “chaotic” dynamics simulates biological pattern recognition. This paper reports the characteristics of the KIII set and applies it to text classification. Compared with conventional pattern recognition algorithms, its accuracy and efficiency are demonstrated in this report on an application to text classification.