Abstract
Based on summing up three kinds of fuzzy inference systems and the functional equivalence between the radial basis function (RBF) networks and fuzzy inference systems, the paper presents a new concept of generalized fuzzy inference and the new model of generalized fuzzy RBF network. Then the generalized learning algorithm is derived. A nonlinear system identification is done by this network. Results have verified that the generalized fuzzy RBF networks have an ability to approximate arbitrary nonlinear function with an arbitrary given accuracy and the learning algorithm described in the paper is effective and available.
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