ＲＢＦ出力素子を用いたモジュール型ニューラルネット

• 石原 聖司

  法政大学工学部経営工学科

• 永野 俊

  法政大学工学部経営工学科

書誌事項

タイトル別名

• A Modular-Type Neural Network with RBF Output Units.

抄録

Recently, modular networks have been used to try to solve efficiently multiclass classification problems. However, the rejection rate on patterns of unlearned classes is usually very low. Moreover, when new classes are later added, old modules in the usual modular network need to be re-trained. A modular network proposed in this paper has RBF output units and an algorithm for incremental learning that improve these points. The results of computer simulations showed that the model achieved higher rejection rates on patterns of unlearned classes than the usual modular networks.

収録刊行物

• 日本神経回路学会誌

  日本神経回路学会誌 6 (4), 203-217, 1999

  日本神経回路学会

詳細情報

• CRID: 1390001204463977344
• NII論文ID: 10010424371
• NII書誌ID: AA11658570
• DOI: 10.3902/jnns.6.203
• ISSN: 18830455
• ISSN: 1340766X
• 本文言語コード: ja
• 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