Abstract
Radial basis function (RBF) networks represent a fundamentally different architecture from what we have seen in the previous chapters. All the previous chapters use a feed-forward network in which the inputs are transmitted forward from layer to layer in a similar fashion in order to create the final outputs.
“Two birds disputed about a kernel, when a third swooped down and carried it off.”—African Proverb
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Aggarwal, C.C. (2018). Radial Basis Function Networks. In: Neural Networks and Deep Learning. Springer, Cham. https://doi.org/10.1007/978-3-319-94463-0_5
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DOI: https://doi.org/10.1007/978-3-319-94463-0_5
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