Multi-modular neural networks for the classification of e+e− hadronic events

Abstract Some multi-modular neural network methods of classifying e + e − hadronic events are presented. We compare the performances of the following neural networks: MLP (multilayer perceptron), MLP and LVQ (learning vector quantization) trained sequentially, and MLP and RBF (radial basis function) trained sequentially. We introduce a MLP-RBF cooperative neural network. Our last study is a multi-MLP neural network.