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An alternative approach to solve convergence problems in the backpropagation algorithm

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3 Author(s)
Goedtel, A. ; Dept. of Electr. Eng., State Univ. of Sao Paulo, Brazil ; da Silva, I.N. ; Semi, P.J.A.

The multilayer perceptron network has become one of the most used in the solution of a wide variety of problems. The training process is based on the supervised method, where the inputs are presented to the neural network and the output is compared with a desired value. However, the algorithm presents convergence problems when the desired output of the network has small slope in the discrete time samples or the output is a quasi-constant value. The proposal of this paper is presenting an alternative approach to solve this convergence problem with a pre-conditioning method of the desired output data set before the training process and a post-conditioning when the generalization results are obtained. Simulations results are presented in order to validate the proposed approach.

Published in:

Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on  (Volume:2 )

Date of Conference:

25-29 July 2004