Generalization ability of neural networks is the most important criterion to determine whether one algorithm is powerful or not. Many new algorithms have been devised to enhance the generalization ability of neural networks. In this paper a new algorithm using the Gram-Schmidt orthogonalization algorithm  to the outputs of nodes in the hidden layers is proposed with the aim to reduce the interference among the nodes in the hidden layers, which is much more efficient than the regularizers methods. Simulation results confirm the above assertion.
|出版ステータス||Published - 2001 1 1|
|イベント||International Joint Conference on Neural Networks (IJCNN'01) - Washington, DC, United States|
継続期間: 2001 7 15 → 2001 7 19
|Conference||International Joint Conference on Neural Networks (IJCNN'01)|
|Period||01/7/15 → 01/7/19|
ASJC Scopus subject areas