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Learning in Deep Radial Basis Function Networks [PDF]
EntropyLearning in neural networks with locally-tuned neuron models such as radial Basis Function (RBF) networks is often seen as instable, in particular when multi-layered architectures are used. Furthermore, universal approximation theorems for single-layered
Fabian Wurzberger, Friedhelm Schwenker
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Radial Basis Function Finite Difference Method Based on Oseen Iteration for Solving Two-Dimensional Navier–Stokes Equations [PDF]
Entropy, 2023 In this paper, the radial basis function finite difference method is used to solve two-dimensional steady incompressible Navier–Stokes equations. First, the radial basis function finite difference method with polynomial is used to discretize the spatial ...
Liru Mu, Xinlong Feng
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Mathematics, 2021 The study develops the displacement error recovery method in a mesh free environment for the finite element solution employing the radial point interpolation (RPI) technique. The RPI technique uses the radial basis functions (RBF), along with polynomials
Mohd. Ahmed +3 more
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Radial Basis Function Pseudospectral Method for Solving Standard Fitzhugh-Nagumo Equation [PDF]
International Journal of Mathematical, Engineering and Management Sciences, 2020 In this article, a pseudospectral approach based on radial basis functions is considered for the solution of the standard Fitzhugh-Nagumo equation. The proposed radial basis function pseudospectral approach is truly mesh free.
Geeta Arora, Gurpreet Singh Bhatia
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Entropy, 2022 In this paper, we present a fully Lagrangian method based on the radial basis function (RBF) finite difference (FD) method for solving convection–diffusion partial differential equations (PDEs) on evolving surfaces.
Nazakat Adil, Xufeng Xiao, Xinlong Feng
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Application of Basis Functions for Hull Form Surface Modification
Journal of Marine Science and Engineering, 2021 Basis functions are key in constructing interpolation equations in hull surface modification based on radial basis functions (RBF) interpolation. However, few have studied the selection of basis functions in depth.
Baiwei Feng +4 more
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Radial basis function‐based exoskeleton robot controller development
IET Cyber-systems and Robotics, 2022 The realisation of a model‐based controller for a robot with a higher degree of freedom requires a substantial amount of computational power. A high‐speed CPU is required to maintain a higher sampling rate.
SK Hasan
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Scaling of radial basis functions
IMA Journal of Numerical Analysis, 2023 Abstract This paper studies the influence of scaling on the behavior of radial basis function interpolation. It focuses on certain central aspects, but does not try to be exhaustive. The most important questions are: How does the error of a kernel-based interpolant vary with the scale of the kernel chosen?
Larsson, Elisabeth, Schaback, Robert
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Radial Basis Function Cascade Correlation Networks
Algorithms, 2009 A cascade correlation learning architecture has been devised for the first time for radial basis function processing units. The proposed algorithm was evaluated with two synthetic data sets and two chemical data sets by comparison with six other standard
Peter de B. Harrington, Weiying Lu
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Radial Basis Function Nets for Time Series Prediction [PDF]
International Journal of Computational Intelligence Systems, 2009 This paper introduces a novel ensemble learning approach based on recurrent radial basis function networks (RRBFN) for time series prediction with the aim of increasing the prediction accuracy. Standing for the base learner in this ensemble, the adaptive
Abdelhamid Bouchachia
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