A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
The Pade Approximant Based Network for Variational Problems
[article]
2020
arXiv
pre-print
In solving the variational problem, the key is to efficiently find the target function that minimizes or maximizes the specified functional. In this paper, by using the Pade approximant, we suggest a methods for the variational problem. By comparing the method with those based on the radial basis function networks (RBF), the multilayer perception networks (MLP), and the Legendre polynomials, we show that the method searches the target function effectively and efficiently.
arXiv:2004.00711v1
fatcat:i6kiyjnzf5a5fd5kx2d7lxz4xe