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Therefore, a back propagation network propagates error information top-down to each layer of RBM and fine-tunes the whole DBN network.
In the traditional method, relation transitivity is a basic assumption in the change propagation network.
The ANN was then designed and trained online by employing a back propagation network (BPN) algorithm.
A back propagation network (BPN) is proposed to verify the mapping of sneakers onto point guards.
The Back Propagation Network (BPN) is one of the most widely used neural networks.
Then selected descriptors were used as inputs for artificial neural networks with three different weight update functions including Levenberg Marquardt back propagation network (LM-ANN), resilient back propagation network (RP-ANN) and variable learning rate algorithm (GDX-ANN).
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The ANN is adapted from a Feed-Forward Back-Propagation network with delayed output feed-back.
The back-propagation network (BPN) can be used in various fields.
Subsequently, the calibrated heuristic algorithm is used to optimize a back-propagation network (BPN).
Finally, the back-propagation network model is adopted as a classifier.
In this paper, the simulation results are compared with DT, back-propagation network (BPN), and support vector machine (SVM).
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