Classificability-regulated self-organizing map using restricted RBF

In this paper, we propose a hierarchical neural network similar to the Radial Basis Function (RBF) Network. The proposed Restricted RBF (rRBF) executes a neighborhood-restricted activation function for its hidden neurons and consequently generates a unique topological map, which differs from the conventional Self-Organizing Map, in its internal layer. The primary objective of this study is to visualize and study the emergence of order in the structure and investigate the relation between the order and the learning performance of a hierarchical neural network.