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.
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Zhang, J., Li, G., Freeman, W.J. (2006). Application of Novel Chaotic Neural Networks to Text Classification Based on PCA. In: Chang, LW., Lie, WN. (eds) Advances in Image and Video Technology. PSIVT 2006. Lecture Notes in Computer Science, vol 4319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949534_104
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DOI: https://doi.org/10.1007/11949534_104
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68297-4
Online ISBN: 978-3-540-68298-1
eBook Packages: Computer ScienceComputer Science (R0)