非単調ニューロンを用いて相関学習された連想記憶モデルのＳ／Ｎ解析

• 木本 智幸

  大分工業高等専門学校

• 小泉 耕二

  大阪大学基礎工学部

• 岡田 真人

  科学技術振興事業団

書誌事項

タイトル別名

• S/N Analysis of Associative Memory Model based on Correlation Learning using a Non-Monotonic Property

抄録

An associative memory model based on the correlation method using a non-monotonic neuron property is proposed and investigated by signal-to-noise analysis. The signal term for recalling and the cross-talk noise term preventing recalling are negatively correlated with each other in this model, so that the variance of the internal potential becomes much smaller than that of the cross-talk noise. This is contrasted with the situation of the Hopfield model in which the two terms are independent of each other. As a result, the present model has twice larger storage capacity in comparison with the Hopfiled model.

収録刊行物

• 日本神経回路学会誌

  日本神経回路学会誌 8 (3), 86-93, 2001

  日本神経回路学会

詳細情報

• CRID: 1390282679440497664
• NII論文ID: 10010424565
• NII書誌ID: AA11658570
• DOI: 10.3902/jnns.8.86
• 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