連想能力を改善するニュ-ラルネットワ-クの拡張構成

• 大西 竜太

  神戸大学工学部 シャープ(株)

• 藤崎 泰正

  シャープ(株)

• 平井 一正

  シャープ(株)

書誌事項

タイトル別名

• An Expanding Construction of Neural Networks Improving Associative Ability
• レンソウ ノウリョク オ カイゼンスル ニューラル ネットワーク ノ カクチョ

抄録

In this paper, we propose an expanding construction of neural networks to improve associative ability when we use the projection rule to memorize prototype vectors in the networks. In order to embed the prototype vectors in the high order networks, we add an arbitrary fixed pattern to each prototype vector at the memorizing process and add it to each key vector at the recalling process. The associative ability is concerned with the domain of attraction of each equilibrium corresponding to each prototype vector. We evaluate the domain of attraction of the networks and prove that the domain of attraction of the expanded networks is larger than that of the non-expanded networks. The evaluation of the domain of attraction depends only on the order of added pattern. The simulation results show the quantitative relations between the order of the networks and the domain of attraction.

収録刊行物

• システム制御情報学会論文誌

  システム制御情報学会論文誌 7 (12), 498-504, 1994

  一般社団法人 システム制御情報学会

キーワード

• associative memory
• neural network
• expanding construction
• domain of atraction
• projection rule

詳細情報

• CRID: 1390282680142237824
• NII論文ID: 10007138420
• NII書誌ID: AN1013280X
• DOI: 10.5687/iscie.7.498
• ISSN: 2185811X
• ISSN: 13425668
• NDL書誌ID: 3900009
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I3900009
• データソース種別:
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• 抄録ライセンスフラグ: 使用不可