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论文类型：期刊论文

发表时间：2007-03-01

发表刊物：Journal of Information and Computational Science

收录刊物：EI

卷号：4

期号：1

页面范围：251-255

ISSN号：15487741

摘要：Gradient algorithm has been widely used as a learning algorithm for training the weights of feedforward neural networks. A simple criterion is used to choose the learning rate during each cycle of training iteration. A convergence result of the corresponding batch gradient algorithm and the monotonicity error function in the iteration are proved, which are stronger than the usual results for general optimization problems. A supporting numerical experiment is also presented.