Hierarchical Learning Algorithm for the Beta Basis Function Neural Network
Neural and Evolutionary Computing
2012-10-31 v1 Artificial Intelligence
Abstract
The paper presents a two-level learning method for the design of the Beta Basis Function Neural Network BBFNN. A Genetic Algorithm is employed at the upper level to construct BBFNN, while the key learning parameters :the width, the centers and the Beta form are optimised using the gradient algorithm at the lower level. In order to demonstrate the effectiveness of this hierarchical learning algorithm HLABBFNN, we need to validate our algorithm for the approximation of non-linear function.
Cite
@article{arxiv.1210.8124,
title = {Hierarchical Learning Algorithm for the Beta Basis Function Neural Network},
author = {Habib Dhahri and Mohamed Adel Alimi},
journal= {arXiv preprint arXiv:1210.8124},
year = {2012}
}