Abstract
This paper develops the incremental learning by using chaotic neurons, which is called “on-demand learning” at its developing time. The incremental learning unites the learning process and the recall process in the associative memories. This learning method uses the features of the chaotic neurons which were first developed by Prof. Aihara. The features include the spatio-temporal sum of the inputs and the refractoriness in neurons. Because of the temporal sum of the inputs, the network learns from inputs with noises. But, it is not obvious that the refractoriness is needed to the incremental learning. In this paper, the computer simulations investigate how the refractoriness takes an important part in the incremental learning. The results of the simulations, show that the refractoriness is an essential factor, but that strong refractoriness causes failures to learn patterns.
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References
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© 2004 Springer-Verlag Berlin Heidelberg
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Deguchi, T., Ishii, N. (2004). On Refractory Parameter of Chaotic Neurons in Incremental Learning. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30133-2_14
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DOI: https://doi.org/10.1007/978-3-540-30133-2_14
Publisher Name: Springer, Berlin, Heidelberg
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