Research on the Method of Neural Network Modeling Based on FCM Algorithm and Its Application on Vision-based Sensors

Abstract

This paper proposes a novel fuzzy neural network model based on fuzzy clustering method. The model can accept continuous and discrete inputs together; the discrete input to the model is divided into several clusters by using fuzzy c-mean clustering algorithm (FCM). A fuzzy clustering neuron (FC-neuron) is designed to calculate a membership degree value belonging to one cluster for each discrete input. A four-layer hybrid neural network is constructed; fuzzy-neurons and FC-neurons construct the antecedent part of fuzzy rules. A multi-input multioutput hybrid neural network was designed by the novel modeling method and applied to vision-based sensors. Simulation results show this method is superior to the traditional neural network model in vision-based sensors.