Abstract
Combined CMAC addressing schemes with fuzzy logic idea, a general fuzzified CMAC (GFAC) is proposed, in which the fuzzy membership functions are utilized as the receptive field functions. The mapping of receptive field functions, the selection law of membership with its parameters and the learning algorithm are presented. By using GFAC, the approximation of complex functions can be obtained which is more continuous than using conventional CMAC. The simulation results show that GFAC has good generalization, proper approximate accuracy and capacity to calculate function differential output.
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Shen, Z., Guo, C. (2012). A General Fuzzified CMAC and Its Function Approximation. In: Xie, A., Huang, X. (eds) Advances in Computer Science and Education. Advances in Intelligent and Soft Computing, vol 140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27945-4_17
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DOI: https://doi.org/10.1007/978-3-642-27945-4_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27944-7
Online ISBN: 978-3-642-27945-4
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