Abstract
In this paper, a physiological fuzzy neural network is proposed, which shows more improved learning time and convergence property than that of the conventional fuzzy neural network. First, we investigate the structure of physiological neurons of the nervous system and propose new neuron structure based on fuzzy logic. And by using the proposed fuzzy neuron structures, the model and learning algorithm of physiological fuzzy neural network are proposed. We applied the proposed algorithm to 3-bit parity problem. The experiment results showed that the proposed algorithm reduces the possibility of local minima more than the conventional single layer perceptron does, and improves the time and convergence for learning.
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References
Gupta, M.M., Qi, J.: On fuzzy Neuron Models. Proceedings of IJCNN 2, 431–435 (1991)
Lin, C.T., Lee, C.S.G.: Neural network based fuzzy logic control and decision system. IEEE Trans. on Computer C-40(12), 1320–1336 (1991)
Kim, K.B., Joo, Y.H., Cho, J.H.: An Enhanced Fuzzy Neural Network. In: Liew, K.-M., Shen, H., See, S., Cai, W. (eds.) PDCAT 2004. LNCS, vol. 3320, pp. 176–179. Springer, Heidelberg (2004)
Kuffer, S.W., Nicholls, T.G., Martin, A.R.: Form Neuron to Brain: A Cell Approach to the function of Nervous System, 2nd edn. Sunderland, Mass. Sinauer (1984)
Kim, K.B., Seo, C.J., Yang, H.K.: A Biological Fuzzy Multilayer Perceptron Algorithm. International Journal of Maritime Information and Communication Sciences 1(3), 104–108 (2003)
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Kim, KB., Bea, HR., Kim, CS. (2005). A Physiological Fuzzy Neural Network. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_149
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DOI: https://doi.org/10.1007/11539902_149
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28320-1
Online ISBN: 978-3-540-31863-7
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