Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4633124 | Applied Mathematics and Computation | 2008 | 6 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Jun-fei Qiao, Ying Zhang, Hong-gui Han,