Approximation by spherical neural networks with zonal functions

Authors

  • Zhixiang Chen Shaoxing University
  • Feilong Cao China Jiliang University

DOI:

https://doi.org/10.21914/anziamj.v58i0.11098

Keywords:

approximation, neural networks, zonal function, error.

Abstract

We address the construction and approximation for feed-forward neural networks (FNNs) with zonal functions on the unit sphere. The filtered de la Vallée-Poussin operator and the spherical quadrature formula are used to construct the spherical FNNs. In particular, the upper and lower bounds of approximation errors by the FNNs are estimated, where the best polynomial approximation of a spherical function is used as a measure of approximation error. doi:10.1017/S1446181117000104

Author Biographies

Zhixiang Chen, Shaoxing University

Department of Mathematics

Feilong Cao, China Jiliang University

Department of Applied Mathematics

Published

2017-07-20

Issue

Section

ANZIAM-ZPAMS Joint Meeting