Dynamic associative memory by using chaos of a simple associative memory model with Euler's finite difference scheme

Kazuaki Masuda, Eitaro Aiyoshi

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Associative memories are capable of memorizing particular patterns and recalling them from their partial information. Different from simple associative memory models based on Hopfield neural networks with sigmoid neurons, a particular model based on the chaotic neural network was also proposed for dynamic associative memory, which can generate various patterns from given information. However, the chaotic network model is so complicated that its behavior has not been analyzed well and can't be controlled easily. To the contrary, this paper shows that a discrete-time simple associative memory model with Euler's difference scheme has possibility to generate chaos. It follows that even such a simple model can be used for dynamic associative memory. Numerical examples also confirm the emergence of chaotic trajectories of the model and demonstrate their use for dynamic associative memory.

本文言語English
ホスト出版物のタイトルProceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers
出版社Society of Instrument and Control Engineers (SICE)
ページ1444-1450
ページ数7
ISBN(印刷版)9784907764364
出版ステータスPublished - 2010 1月 1

出版物シリーズ

名前Proceedings of the SICE Annual Conference

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

フィンガープリント

「Dynamic associative memory by using chaos of a simple associative memory model with Euler's finite difference scheme」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル