RCCN: radial basis competitive and cooperative network

Abstract

The radial basis bidirectional competitive and cooperative network (RCCN) is a bidirectional mapping network that accommodates and generates radial basis function units (RBFUs) with the help of efficient use of the accommodation boundaries. The analysis and simulation show that the automatic generation scheme provides the necessary and sufficient enhancement of the network, the hierarchical learning scheme ensures the desired accuracy in mapping, the mapping scheme processes the many-to-many relation for both directions with sufficient accuracy, and using ellipsoidal boundaries is more efficient and flexible compared to circles. RCCN may create an enormous number of RBFUs and degenerate in accuracy by learning with noisy samples. However, greater efficiency can be expected if RBFUs are allowed to have individual accommodation boundary sizes under the optimal learning scheme.<>