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45 094 (0,355s)

Result

Capabilities of Radial and Kernel Networks

will be illustrated by the paradigmatic examples of Gaussian kernel and radial networks. units called perceptrons. Later, other types of units became popular in neurocomputing due to their good mathematic...

IN - Informatika

  • 2013
  • D
Result

Accuracy of approximations of solutions to Fredholm equations by kernel methods

theory. The results are applied to networks with Gaussian and kernel unitsApproximate solutions to inhomogeneous Fredholm integral equations of the second kind by radial and kernel networks are investigat...

IN - Informatika

  • 2012
  • Jx
  • Link
Result

Comparing Fixed and Variable-Width Gaussian Networks

is investigated: Gaussian radial basis- functions (RBFs) where both widths and centers vary and Gaussian kernel networks which have fixed widths but varying centers. The effect in reproducing kernel Hilbe...

IN - Informatika

  • 2014
  • Jx
  • Link
Result

Bounds for Approximate Solutions of Fredholm Integral Equations Using Kernel Networks

Approximation of solutions of integral equations by networks with kernel units is investigated theoretically. There are derived upper bounds on speed of decrease of errors in approximation of solutions of Fredholm integral equations...

IN - Informatika

  • 2011
  • D
  • Link
Result

Gaussian Radial and Kernel Networks with Varying and Fixed Widths

The role of widths of Gaussians in computational models which they generate is investigated. Suitability of Gaussian kernel models with fixed widths for regression on widths of Gaussian kernels and the inp...

IN - Informatika

  • 2013
  • D
Result

Some Comparisons of Radial and Kernel Computational Models

in neurocomputing, radial-basis function networks (RBF) and kernel models, are compared. Both. We investigate these two types of models in the framework of kernel units complexity. On the other hand, kernel

IN - Informatika

  • 2011
  • D
Result

Kernel Networks with Fixed and Variable Widths

The role of width in kernel models and radial-basis function networks is investigated with a special emphasis on the Gaussian case. Quantitative bounds are given on kernel-based regularization showing the effect of...

IN - Informatika

  • 2011
  • D
  • Link
Result

Some Comparisons of Networks with Radial and Kernel Units

Two types of computational models, radial-basis function networks with units having varying widths and kernel networks where all units have a fixed width, are investigated in the framework of scaled kernels

IN - Informatika

  • 2012
  • D
Result

Multivariable Approximation by Convolutional Kernel Networks

Computational units induced by convolutional kernels together with biologically inspired perceptrons belong to the most widespread types of units used in neurocomputing. Radial convolutional kernels with v...

IN - Informatika

  • 2016
  • D
  • Link
Result

Translation-Invariant Kernels for Multivariable Approximation

kernel units for function approximation and classification tasks is investigated. It is shown that a critical property influencing the capabilities of kernel networks is how the Fourier transforms of kernels conve...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2021
  • Jimp
  • Link
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