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 ✦
Evolutionary system for automatically constructing and adapting radial basis function networks
✍ Scribed by Daniel Manrique; Juan Ríos; Alfonso Rodríguez-Patón
- Book ID
- 113814151
- Publisher
- Elsevier Science
- Year
- 2006
- Tongue
- English
- Weight
- 466 KB
- Volume
- 69
- Category
- Article
- ISSN
- 0925-2312
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