Convergence of BP algorithm for product unit neural networks with exponential weights
نویسندگان
چکیده
Product unit neural networks with exponential weights (PUNNs) can provide more powerful internal representation capability than traditional feed-forward neural networks. In this paper, a convergence result of the back-propagation (BP) algorithm for training PUNNs is presented. The monotonicity of the error function in the training iteration process is also guaranteed. A numerical example is given to support the theoretical findings. r 2008 Elsevier B.V. All rights reserved. MSC: 92B20; 68Q32; 74P05
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ورودعنوان ژورنال:
- Neurocomputing
دوره 72 شماره
صفحات -
تاریخ انتشار 2008