IEEE

Nonlinear Gaussian filtering via radial basis function approximation

Abstract: This paper presents a novel type of Gaussian filter - the radial basis Gaussian filter (RB-GF) - for nonlinear state estimation. In the RB-GF, we propose to use radial basis functions (RBFs) ...
IEEE

Gaussian radial basis functions and indexed families of functionals

Abstract: In this paper, we report on results concerning the capabilities of Gaussian radial basis function networks in the setting of inner product spaces that need not be finite dimensional.
GitHub

Plots of GRBF and GGRBF Kernels.m

title('Generalized Gaussian Radial Basis Function Kernel; $\sigma=\frac{1}{2}$, $\sigma_0=\frac{1}{0.98}$','Interpreter','latex') contourf(X,Y,GG,50),colorbar ...
Risk

A k-means++-improved radial basis function neural network model for corporate financial crisis early warning: an empirical model validation for Chinese listed companies

An early warning of corporate financial crises has long been the focus of investors and enterprises. Integrated early warning models for financial crises perform better than normal models, but most ...
JSTOR Daily

Efficient Bayesian Hierarchical Functional Data Analysis with Basis Function Approximations Using Gaussian-Wishart Processes

Functional data are defined as realizations of random functions (mostly smooth functions) varying over a continuum, which are usually collected on discretized grids with measurement errors. In order ...