This paper proposes a radial basis function neural network (RBFNN), called the q-Gaussian RBFNN, that reproduces different radial basis functions (RBFs) by means of a real parameter q. The architecture, weights and node topology are learnt through a hybrid algorithm (HA). In order to test the overal
✦ LIBER ✦
Relation between generalized radial basis function (GRBF) networks and neural networks
✍ Scribed by Akio Miyazaki; Tsuyoshi Yamada
- Book ID
- 112079618
- Publisher
- John Wiley and Sons
- Year
- 1993
- Tongue
- English
- Weight
- 587 KB
- Volume
- 76
- Category
- Article
- ISSN
- 1042-0967
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