Radial basis function neural network (RBFN) has the power of the universal function approximation. But how to construct an RBFN to solve a given problem is usually not straightforward. This paper describes a method to construct an RBFN classifier efficiently and effectively. The method determines th
Sensitivity analysis applied to the construction of radial basis function networks
β Scribed by D. Shi; D.S. Yeung; J. Gao
- Publisher
- Elsevier Science
- Year
- 2005
- Tongue
- English
- Weight
- 134 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0893-6080
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π SIMILAR VOLUMES
coordinate Multiquadric approximation scheme Numerical comparison of the solutions Condition number a b s t r a c t This paper introduces a variant of direct and indirect radial basis function networks (DRBFNs and IRBFNs) for the numerical solution of Poisson's equation. We use transformation from
## Abstract A new approach, based on the radialβbias function neural network (RBFβNN) combined with wavelet transform, is presented for the estimation of the locations and radii of conducting cylindrical scatterers. The discrete wavelet transform coefficients of the electricβfield values scattered