Effective Training of RBF Networks

RBF networks seem to be an interesting and efficient alternative for traditional sigmoid-based neural networks. More sophisticated activation function makes a network more powerful but requires developing of new training methods. The paper presents a new more efficient training algorithm based on the second-order constructive ErrCor (Error Correction) algorithm. The effectiveness of the proposed approach has been confirmed by several experiments with both approximation and classification problems.