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A consideration on the learning algorithm of neural network-utilization of the hierarchical structure stochastic automata for the backpropagation method with momentum

机译:势头对势势的反向桥墩方法的神经网络利用学习算法考虑

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Backpropagation (BP) method with momentum has often been applied to adapt artificial neural networks for various pattern classification problems. However, an important limitation of this method is that its learning performance depends heavily upon the selection of the values of momentum factor and step size. In this paper, it is shown that the hierarchical structure stochastic automata can be used for finding appropriate values of the parameters involved in the BP method with momentum.
机译:具有势头的BackPropagation(BP)方法通常应用于适应各种模式分类问题的人工神经网络。然而,这种方法的一个重要限制是其学习性能在很大程度上取决于选择动量因子和步长的值。在本文中,示出了分层结构随机自动机可以用于找到具有动量的BP方法中涉及的参数的适当值。

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