On multivariate Lagrange interpolation
Mathematics of Computation
Pattern recognition using neural networks: theory and algorithms for engineers and scientists
Pattern recognition using neural networks: theory and algorithms for engineers and scientists
On simultaneous approximations by radial basis function neural networks
Applied Mathematics and Computation
Deterministic convergence of an online gradient method for neural networks
Journal of Computational and Applied Mathematics - Selected papers of the international symposium on applied mathematics, August 2000, Dalian, China
A Theory of Networks for Approximation and Learning
A Theory of Networks for Approximation and Learning
IEEE Transactions on Neural Networks
Constructive approximate interpolation by neural networks
Journal of Computational and Applied Mathematics
Constructive approximate interpolation by neural networks
Journal of Computational and Applied Mathematics
Approximate interpolation by neural networks with the inverse multiquadric functions
ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
Constructive approximate interpolation by neural networks in the metric space
Mathematical and Computer Modelling: An International Journal
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We consider multivariate interpolation at arbitrary points and provide effective interpolation formulas by using simple ridge polynomials which essentially possess the nature of univariate polynomials in computation, and show that ridge polynomials with least degree can be found for interpolation purpose, which a computational algorithm is provided correspondingly. We then apply the interpolation results to design a computational algorithm for training feedforward neural networks.