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Training multilayer perceptrons for control systems applications - a comparison of different approaches
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Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large field of applications. In control and signal processing applications, MLPs are mainly used as nonlinear mapping approximators. The most common training algorithm used with MLPs is the error back-propagation (BP) alg. (1).
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Ruano, A. E. Training multilayer perceptrons for control systems applications - a comparison of different approaches, Trabalho apresentado em Int. Conf. on Engineering Applications of Neural Networks (EANN’96), In Int. Conf. on Engineering Applications of Neural Networks (EANN’96), London, 1996.