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Fast unit pruning algorithm for feedforward neural network design

机译:前馈神经网络设计的快速单位修剪算法

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摘要

A fast unit pruning algorithm for feedforward neural network is presented and the way used by the algorithm which based on optimal brain surgeon (OBS) is to remove the unneeded hidden units directly so that carry out the self-organization design on the architecture of neural networks. The algorithm is tested on several modeling problems, and is compared with OBS. It is found that the fast unit pruning algorithm is much more efficient than OBS which can not only reduce the complexity of the network but also accelerate the learning speed. (C) 2008 Elsevier Inc. All rights reserved.
机译:提出了一种前馈神经网络的快速单位修剪算法,该算法基于最优脑外科医生(OBS)的方法是直接去除不需要的隐藏单元,从而对神经网络的架构进行自组织设计。 。该算法经过几个建模问题的测试,并与OBS进行了比较。研究发现,快速单位修剪算法比OBS效率更高,不仅可以降低网络的复杂性,而且可以提高学习速度。 (C)2008 Elsevier Inc.保留所有权利。

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