1. Hybrid learning of RBF networks
- Creator:
- Neruda, Roman and Kudová, Petra
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- neural networks, RBF networks, gradient algorithm, three step learning, and genetic algorithm
- Language:
- English
- Description:
- Three different learning rnethods for RBF networks and their combinations are preserited. Standard gradient learning, three-step algorithm with unsupervised part, and evolutionary algorithm are introduced. Their performance is compared on two benchmark problerns: Two spirals and Iris plants. The results show that the three-step learning is usually the fastest, while the gradient learning achieves better precision. The cornbination of these two approaches gives the best results.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public