Multiple classifiers fusion system based on the radial basis probabilistic neural networks

Abstract

The fusion system designing of multiple classifiers, which is based on the radial basis probabilistic neural network (RBPNN), is discussed in this paper. By means of the proposed design method, the complex structure optimization can be effectively avoided in the designing procedure of the RBPNN. In addition, D-S fusion algorithm adopted in the system greatly improves the classification performance for the complexity problem of the real-world. The simulation results demonstrate that the designing case of the fusion system based on the RBPNNs is feasible and effective. © Springer-Verlag Berlin Heidelberg 2004.