Error bounds for approximation with neural networks
Journal of Approximation Theory
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Approximation accuracy of some neuro-fuzzy approaches
IEEE Transactions on Fuzzy Systems
Approximation bounds for smooth functions in C(Rd) by neural and mixture networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
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A great deal of research has been devoted in recent years to the designing Fuzzy-Neural Networks (FNN) from input-output data. And some works were also done to analyze the performance of some methods from a rigorous mathematical point of view. In this paper, the approximation bound for the clustering method, which is employed to design the FNN with the Bell Membership Function, is established. The detailed formulas of the error bound between the nonlinear function to be approximated and the FNN system designed based on the input-output data are derived.