Pages that link to "Item:Q1422258"

The following pages link to Relaxed conditions for radial-basis function networks to be universal approximators. (Q1422258):

Displaying 20 items.

• Universal approximation by radial basis function networks of Delsarte translates (Q461175) (← links)
• The universal approximation capabilities of double \(2\pi\)-periodic approximate identity neural networks (Q521720) (← links)
• Multilayer perceptrons as function approximators for analytical solutions of the diffusion equation (Q723074) (← links)
• \(L^p\) approximation capability of RBF neural networks (Q944076) (← links)
• A class of universal approximators of real continuous functions revisited (Q1623058) (← links)
• The universal approximation capabilities of cylindrical approximate identity neural networks (Q1639386) (← links)
• Denseness of radial-basis functions in \(L^ 2(R^ n)\) and its applications in neural networks (Q1917815) (← links)
• A comment on ``Relaxed conditions for radial-basis function networks to be universal approximators'' (Q1932117) (← links)
• The rate of approximation of Gaussian radial basis neural networks in continuous function space (Q1940856) (← links)
• Using radial basis function networks for function approximation and classification (Q1954367) (← links)
• Approximation in weighted \(p\)-mean by RBF networks of Delsarte translates (Q2338756) (← links)
• Wiener's tauberian theorems for the Fourier-Bessel transformation and uniform approximation by RBF networks of Delsarte translates (Q2352197) (← links)
• On a problem of Hornik (Q2354173) (← links)
• Control of robots using radial basis function neural networks with dead-zone (Q3019216) (← links)
• Stochastic stability of a neural-net robot controller subject to signal-dependent noise in the learning rule (Q3576981) (← links)
• Radial basis function neural networks of Hankel translates as universal approximators (Q5236750) (← links)
• Computational Science - ICCS 2004 (Q5712555) (← links)
• Automated nonlinear feedforward controller identification applied to engine air path output tracking (Q6593290) (← links)
• RandONets: shallow networks with random projections for learning linear and nonlinear operators (Q6648362) (← links)
• Importance sampling for option pricing with feedforward neural networks (Q6659479) (← links)