caa a22 4500 475800737 CHVBK 20180406123736.0 cr unu---uuuuu 170329e20000801xx s 000 0 eng 10.1023/A:1009621931185 doi (NATIONALLICENCE)springer-10.1023/A:1009621931185 Analysis of the Functional Block Involved in the Design of Radial Basis Function Networks [Elektronische Daten] [I. Rojas, H. Pomares, J. Gonzáles, J. Bernier, E. Ros, F. Pelayo, A. Prieto] The main architectures, learning abilities and applications of radial basis function (RBF) neural networks are well documented. However, to the best of our knowledge, no in-depth analyses have been carried out into the influence on the behaviour of the neural network arising from the use of different alternatives for the design of an RBF (different non-linear functions, distances, number of neurons, structures, etc.). Thus, as a complement to the existing intuitive knowledge, it is necessary to have a more precise understanding of the significance of the different alternatives. In the present contribution, the relevance and relative importance of the parameters involved in such a design are investigated by using a statistical tool, the ANalysis Of the VAriance (ANOVA). In order to obtain results that are widely applicable, various problems of classification, functional approximation and time series estimation are analyzed. Conclusions are drawn regarding the whole set. Kluwer Academic Publishers, 2000 RBF neural networks nationallicence neural networks design nationallicence statistical analysis of RBF nationallicence RBF structures nationallicence Rojas I. Department of Architecture and Computer Technology, University of Granada, Spain aut Pomares H. Department of Architecture and Computer Technology, University of Granada, Spain aut Gonzáles J. Department of Architecture and Computer Technology, University of Granada, Spain aut Bernier J. Department of Architecture and Computer Technology, University of Granada, Spain aut Ros E. Department of Architecture and Computer Technology, University of Granada, Spain aut Pelayo F. Department of Architecture and Computer Technology, University of Granada, Spain aut Prieto A. Department of Architecture and Computer Technology, University of Granada, Spain aut Neural Processing Letters Kluwer Academic Publishers 12/1(2000-08-01), 1-17 1370-4621 12:1<1 2000 12 11063 https://doi.org/10.1023/A:1009621931185 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1009621931185 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Rojas I. Department of Architecture and Computer Technology, University of Granada, Spain aut NATIONALLICENCE 700 1- Pomares H. Department of Architecture and Computer Technology, University of Granada, Spain aut NATIONALLICENCE 700 1- Gonzáles J. Department of Architecture and Computer Technology, University of Granada, Spain aut NATIONALLICENCE 700 1- Bernier J. Department of Architecture and Computer Technology, University of Granada, Spain aut NATIONALLICENCE 700 1- Ros E. Department of Architecture and Computer Technology, University of Granada, Spain aut NATIONALLICENCE 700 1- Pelayo F. Department of Architecture and Computer Technology, University of Granada, Spain aut NATIONALLICENCE 700 1- Prieto A. Department of Architecture and Computer Technology, University of Granada, Spain aut NATIONALLICENCE 773 0- Neural Processing Letters Kluwer Academic Publishers 12/1(2000-08-01), 1-17 1370-4621 12:1<1 2000 12 11063 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer