Hierarchical RBF networks and local parameters estimate

@article{Borghese1998HierarchicalRN,
  title={Hierarchical RBF networks and local parameters estimate},
  author={N. Alberto Borghese and Stefano Ferrari},
  journal={Neurocomputing},
  year={1998},
  volume={19},
  pages={259-283}
}
The method presented here is aimed to a direct fast setting of the parameters of a RBF network for function approximation. It is based on a hierarchical gridding of the input space; additional layers of Gaussians at lower scales are added where the residual error is higher. The number of the Gaussians of each layer and their variance are computed from considerations grounded in the linear filtering theory. The weight of each Gaussian is estimated through a maximum a posteriori estimate carried… CONTINUE READING
Highly Cited
This paper has 67 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 15 extracted citations

67 Citations

01020'98'02'07'12'17
Citations per Year
Semantic Scholar estimates that this publication has 67 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…