Xiaoshuai Ding

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This paper investigates a gradient descent algorithm with penalty for a recurrent neural network. The penalty we considered here is a term proportional to the norm of the weights. Its primary roles in the methods are to control the magnitude of the weights. After proving that all of the weights are automatically bounded during the iteration process, we also(More)
—In order to improve accuracy of fault diagnosis based on SVMs, an improved algorithm of support vector domain description (ISVDD) is proposed, used to pretreat the fault data. ISVDD constructs the recognizer of fault data by introducing an optimal sphere instead of the minimum sphere. The recognizer can sift out the fault data belonging to new unknown(More)
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