On the Use of Neural Network as a Universal Approximator

Neural network process modelling needs the use of experimental design and studies. A new neural network constructive algorithm is proposed. Moreover, the paper deals with the influence of the parameters of radial basis function neural networks and multilayer perceptrons network in process modelling. Particularly, it is shown that the neural modelling, depending on learning approach, cannot be always validated for large classes of dynamic complex processes in comparison with Kolgomorov theorem. keywords. Function approximation, Radial Basis Function (RBF), MultiLayer Perceptron (MLP), Chaotic behaviour.

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