Treinamento distribuído de redes MLP para classificação de figuras geométricas

Abstract

— Multilayer perceptron neural networks are used to classify geometric figures using a distributed approach. Training data are divided among neural networks that communicate through a certain topology, in which each network does not have access to the training data of the others. Simulation results indicate that the performance achieved with distributed training and a suitable topology is similar to that observed with classical training. Thus, data privacy is guaranteed without loss of performance.