We give a generalization of a neural network model originally developed to solve the minimum cardinality vertex covering problem, in order to solve the weighted version of the problem. The model is governed by a modified activation rule and we show that it has some important properties, namely convergence and irredundant covers at stable states. We present experimental results that confirm the effectiveness of the model.