書誌事項
- タイトル別名
-
- Compact Structuring of Hierarchical Neural Networks by Combining Extra Hidden Units
抄録
When we apply a hierarchical neural network based on the back-propagation algorithm to a particular problem, we must determine beforehand the suitable size of network for the problem. But it is a very difficult problem. Too small a network will not learn at all, while too large a network will be inefficient and worsen its generalization ability due to overfitting.<br>In order to solve this problem, in this paper we propose a compact structuring method based on learning with a large size network and then compacting gradually the suitable size network by combining extra hidden units. The result is a small and efficient network that performs better than the original. Also we demonstrate the effectiveness of this method by appling it to two problems, i. e., to identify a logic function and to recognize handwriting characters.
収録刊行物
-
- 計測自動制御学会論文集
-
計測自動制御学会論文集 28 (4), 519-527, 1992
公益社団法人 計測自動制御学会
- Tweet
キーワード
詳細情報 詳細情報について
-
- CRID
- 1390282679478395264
-
- NII論文ID
- 130003970013
-
- ISSN
- 18838189
- 04534654
- http://id.crossref.org/issn/04534654
-
- データソース種別
-
- JaLC
- Crossref
- CiNii Articles
-
- 抄録ライセンスフラグ
- 使用不可