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Approximate Interpolation by Neural Networks with the Inverse Multiquadric Functions
2007For approximate interpolation, a type of single-hidden layer feedforward neural networks with the inverse multiquadric activation function is presented in this paper. We give a new and quantitative proof of the fact that a single layer neural networks with n+1 hidden neurons can learn n + 1 distinct samples with zero error.
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Modified multiquadric methods for scattered data interpolation over a sphere
Computer Aided Geometric Design, 1990Helmut Pottmann
exaly
Multivariate quasi-interpolation schemes for dimension-splitting multiquadric
Applied Mathematics and Computation, 2005Leevan Ling
exaly
Analysis of anisotropic plate using multiquadric radial basis function
Engineering Analysis With Boundary Elements, 2007R K Misra
exaly
Fast Evaluation of Multiquadric RBF Sums by a Cartesian Treecode
SIAM Journal of Scientific Computing, 2011Robert Krasny
exaly

