Nonlinear systems can be modeled by neural networks. However choice of suitable network architecture is the most important problem. And 'how to find the best activation function' is a persistent aspect of the architecture design. Here we have proposed a sigmoid function with one parameter which provides us not only the reduction of error bound but also the opportunity of obtaining better insight into the systems.
|出版物ステータス||出版済み - 12 1 1994|
|イベント||Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94) - St. Louis, MO, USA|
継続期間: 11 13 1994 → 11 16 1994
|会議||Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94)|
|市||St. Louis, MO, USA|
|期間||11/13/94 → 11/16/94|
All Science Journal Classification (ASJC) codes