Voronovskaya type asymptotic expansions for multivariate quasi-interpolation neural network operators

George Anastassiou

doi:10.4067/S0719-06462014000200002

Voronovskaya type asymptotic expansions for multivariate quasi-interpolation neural network operators

Authors

George Anastassiou Department of Mathematical Sciences, University of Memphis, Memphis, TN 38152, U.S.A.

DOI:

https://doi.org/10.4067/S0719-06462014000200002

Keywords:

Multivariate Neural Network Approximation, multivariate Voronovskaya type asymptotic expansion

Abstract

Here we study further the multivariate quasi-interpolation of sigmoidal and hyperbolic tangent types neural network operators of one hidden layer. We derive multivariate Voronovskaya type asymptotic expansions for the error of approximation of these operators to the unit operator.

Downloads

Download data is not yet available.

Downloads

Published

2014-06-01

How to Cite

[1]

G. Anastassiou, “Voronovskaya type asymptotic expansions for multivariate quasi-interpolation neural network operators”, CUBO, vol. 16, no. 2, pp. 33–47, Jun. 2014.