Abstract
A hybrid training method for the radial basis function (RBF) network is presented. The method applies the Kohonen’s self-organizing map (SOM) and a modified learning vector quantization (LVQ) algorithms. Learning algorithms are derived for two alternative RBF network structures exploiting local Gaussian basis functions. The potential of the proposed methods is demonstrated by a function approximation example.
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References
S. Chen, C.F. N. Cowan and P.M. Cowan: IEEE Trans Neural Networks 2, 302 (1991)
D. Fox, V. Heinze, K. Möller, S. Thrun, and G. Veenker, Artificial Neural Networks, T. Kohonen, K. Mäkisara, O. Simula, and J. Kangas (eds.) 201, 1991.
J.-S. Jang: IEEE Trans. Neural Networks, 23, 665 (1993)
T. Kohonen: Self-organization and Associative Memory, 2nd ed., Berlin: Springer Verlag 1988.
T. Kohonen: Proc. IEEE, 1464 (1990)
T. Kohonen, Proc. Int. Joint Conf. Neural Networks, TIJCNN-90 I, 545 (1990)
S. Lee and R. M. Kil: Neural Networks 4, 207 (1991)
J. Moody and C. J. Darken: Neural Computation 1, 281 (1989)
H. Ritter, T. Martinez, and K. Schulten: IEEE Trans. Neural Networks 1, 131 (1990)
H. Ritter, Artificial Neural Networks, T. Kohonen, K. Mäkisara, O. Simula and J. Kangas (eds.) 379, 1991.
P. Vuorimaa: Fuzzy Sets and Systems 66, 223 (1994)
L.-X. Wang and J. M. Mendel: IEEE Trans. Neural Networks 3, 807 (1992)
IXXX studies of the self-organizing map (SOM) and learning vector quantization (LVQ). Helsinki University of Technology, Laboratory of Computer and Information Science, 1995. Available at the internet address 130.233.168.48 via anonymous FTP.
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Ojala, T., Vuorimaa, P. (1995). Modified Kohonen’s Learning Laws for RBF Network. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_93
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DOI: https://doi.org/10.1007/978-3-7091-7535-4_93
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82692-8
Online ISBN: 978-3-7091-7535-4
eBook Packages: Springer Book Archive