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Fault tolerance is one interesting property of artificial neural networks. However, the existing fault models are able to describe limited node fault situations only, such as stuck-at-zero and stuck-at-one. There is no general model that is able to describe a large class of node fault situations. This paper studies the performance of faulty radial basis function (RBF) networks for the general node...
In order to realize automatically classifying can defects and improve the convergence speed and the classification accuracy of Self-Organizing Feature Map (SOFM) neural network, 5 improved measures are presented in this paper. They include using typical sample vector, introducing frequency sensitive factor, learning rate adaptive adjustment, selecting convergence criterion and searching winning neuron...
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