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Sliding mode backpropagation: control theory applied to neural network learning

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3 Author(s)
Parma, G.G. ; Dept. de Engenharia Eletronica, Univ. Fed. de Minas Gerais, Belo Horizonte, Brazil ; Menezes, B.R. ; Braga, A.P.

This paper shows two different methodologies, both based on sliding mode control to train multilayer perceptron. These two methods are compared with standard back propagation, momentum and RPROP algorithms. The results show that the use of this control theory can reduce the time to train multilayer perceptron and also provide an interesting tool to analyze the limits for the parameters involved in the algorithm

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Neural Networks, 1999. IJCNN '99. International Joint Conference on  (Volume:3 )

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