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A radial basis function network (RBFN) for function approximation
(IEEE, 1999-01-01)
A radial basis function network (RBFN) circuit for function approximation is presented. Simulation and experimental results show that the network has good approximation capabilities. The RBFN was a squared hyperbolic secant ...
Multipoint Padé approximants as limits of rational functions of best approximation in the complex domain
(Universidad de Jaén, 2018-10)
In this paper we study the behavior of best Lp-approximations by rational functions to an analytic function on union of disks, when the measure of them tends to zero.
Comparative study between powers of sigmoid functions, MLP-backpropagation and polynomials in function approximation problems
(Spie - Int Soc Optical Engineering, 1999-01-01)
Function approximation is a very important task in environments where the computation has to be based on extracting information from data samples in real world processes. So, the development of new mathematical model is a ...
Function approximation by polynomial wavelets generated from powers of sigmoids
(Spie - Int Soc Optical Engineering, 1996-01-01)
Comparative study between powers of sigmoid functions, MLP-backpropagation and polynomials in function approximation problems
(Spie - Int Soc Optical Engineering, 2014)
Compensated convexity methods for approximations and interpolations of sampled functions in euclidean spaces: Theoretical foundations
(Society for Industrial and Applied Mathematics, 2016-12)
We introduce Lipschitz continuous and C1;1 geometric approximation and interpolation methods for sampled bounded uniformly continuous functions over compact sets and over complements of bounded open sets in Rn by using ...
Mathematical tests about the existence and applications of PPS-wavelets in function approximation problems
(Spie - Int Soc Optical Engineering, 1998-01-01)
Neural networks and wavelet transform have been recently seen as attractive tools for developing eficient solutions for many real world problems in function approximation. Function approximation is a very important task ...
Mathematical tests about the existence and applications of PPS-wavelets in function approximation problems
(Spie - Int Soc Optical Engineering, 1998-01-01)
Neural networks and wavelet transform have been recently seen as attractive tools for developing eficient solutions for many real world problems in function approximation. Function approximation is a very important task ...
Radial basis function networks with quantized parameters
(2008-09-30)
A RBFN implemented with quantized parameters is proposed and the relative or limited approximation property is presented. Simulation results for sinusoidal function approximation with various quantization levels are shown. ...