  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.
