Fuzzy relations neural network: some preliminary results

In this paper, a neuro-fuzzy model is introduced. The model describes a fuzzy relational "IF-THEN" reasoning scheme using an adaptive structure based on fuzzy relations. Two training schemes for the learning of the parameters based respectively on the backpropagation algorithm and pseudo-inverse matrix technique are illustrated. The model qualities are investigated by a series of simulation examples: function approximation, classification and rule extraction. These preliminary and promising results show that the model has a good performance and that it could be used for complex systems in real world applications.