GitHub

Radial Basis Function-based Kolmogorov-Arnold Networks (RBF-KAN)

This repository implements Radial Basis Function (RBF)-based Kolmogorov-Arnold Networks (KAN), a neural network architecture based on the Kolmogorov-Arnold representation theorem. The design (called ...
IEEE

Successive Radial Basis Function Approximation for Finite-Horizon Nonlinear H∞ Control Problems

Abstract: In this paper, a successive radial basis function (RBF) approximation approach is proposed to solve the Hamilton-Jacobi-Isaacs (HJI) partial differential equation (PDE) associated with ...
IEEE

Nonlinear function approximation using radial basis function neural networks

Abstract: Radial basis function neural networks (RBFNN) which are best suited for nonlinear function approximation, have been successfully applied to a wide range of areas including system modeling.
Scientific Research Publishing

Sarra, S.A. and Kansa, E.J. (2009) Multiquadric Radial Basis Function Approximation Methods for the Numerical Solution of Partial Differential Equations. Computational ...

ABSTRACT: We solve numerically an eigenvalue elliptic partial differential equation (PDE) ranging from two to six dimensions using the generalized multiquadric (GMQ) radial basis functions (RBFs). Two ...
Risk

Numerical simulation and applications of the convection–diffusion–reaction equation with the radial basis function in a finite-difference mode

This paper develops two local mesh-free methods for designing stencil weights and spatial discretization, respectively, for parabolic partial differential equations (PDEs) of ...