منابع مشابه
Stable Gaussian radial basis function method for solving Helmholtz equations
Radial basis functions (RBFs) are a powerful tool for approximating the solution of high-dimensional problems. They are often referred to as a meshfree method and can be spectrally accurate. In this paper, we analyze a new stable method for evaluating Gaussian radial basis function interpolants based on the eigenfunction expansion. We develop our approach in two-dimensional spaces for so...
متن کاملHeterogeneous Radial Basis Function Networks
Radial Basis Function (RBF) networks typically use a distance function designed for numeric attributes, such as Euclidean or city-block distance. This paper presents a heterogeneous distance function which is appropriate for applications with symbolic attributes, numeric attributes, or both. Empirical results on 30 data sets indicate that the heterogeneous distance metric yields significantly i...
متن کاملOn Normalising Radial Basis Function
Normalisation of the basis function activations in a radial basis function (RBF) network is a common way of achieving the partition of unity often desired for modelling applications. It results in the basis functions covering the whole of the input space to the same degree. However, normalisa-tion of the basis functions can lead to other eeects which are sometimes less desireable for modelling ...
متن کاملGrowing Radial Basis Function Networks
This paper presents and evaluates two algorithms for incrementally constructing Radial Basis Function Networks, a class of neural networks which looks more suitable for adtaptive control applications than the more popular backpropagation networks. The rst algorithm has been derived by a previous method developed by Fritzke, while the second one has been inspired by the CART algorithm developed ...
متن کاملFunctional radial basis function networks
There has been recently a lot of interest for functional data analysis [1] and extensions of well-known methods to functional inputs (clustering algorithm [2], non-parametric models [3], MLP [4]). The main motivation of these methods is to benefit from the enforced inner structure of the data. This paper presents how functional data can be used with RBFN, and how the inner structure of the form...
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ژورنال
عنوان ژورنال: Scholarpedia
سال: 2010
ISSN: 1941-6016
DOI: 10.4249/scholarpedia.9837