A Smoothing Interval Neural Network
| Autor: | Dakun Yang, Wei Wu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: | |
| Zdroj: | Discrete Dynamics in Nature and Society, Vol 2012 (2012) |
| Druh dokumentu: | article |
| ISSN: | 1026-0226 1607-887X |
| DOI: | 10.1155/2012/456919 |
| Popis: | In many applications, it is natural to use interval data to describe various kinds of uncertainties. This paper is concerned with an interval neural network with a hidden layer. For the original interval neural network, it might cause oscillation in the learning procedure as indicated in our numerical experiments. In this paper, a smoothing interval neural network is proposed to prevent the weights oscillation during the learning procedure. Here, by smoothing we mean that, in a neighborhood of the origin, we replace the absolute values of the weights by a smooth function of the weights in the hidden layer and output layer. The convergence of a gradient algorithm for training the smoothing interval neural network is proved. Supporting numerical experiments are provided. |
| Databáze: | Directory of Open Access Journals |
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