Knowledge Processing system using Improved Chaotic Associative Memory

Yuko Osana, Masafumi Hagiwara

研究成果: Paper査読

3 被引用数 (Scopus)

抄録

In this paper, we propose a Knowledge Processing system using Improved Chaotic Associative Memory (KPICAM). The proposed KPICAM is based on an Improved Chaotic Associative Memory (ICAM) composed of chaotic neurons. In the conventional chaotic neural network, when a stored pattern is given to the network as an external input continuously, around the input pattern is searched. The ICAM makes use of this property in order to separate superimposed patterns and to deal with many-to-many associations. In this research, the ICAM is applied to knowledge processing in which the knowledge is represented in a form of semantic network. The proposed KPICAM has the following features: (1) it can deal with the knowledge which is represented in a form of semantic network; (2) it can deal with characteristics inheritance; (3) it is robust for noisy input. A series of computer simulations shows the effectiveness of the proposed system.

本文言語English
ページ579-584
ページ数6
DOI
出版ステータスPublished - 2000
イベントInternational Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy
継続期間: 2000 7 242000 7 27

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'2000)
CityComo, Italy
Period00/7/2400/7/27

ASJC Scopus subject areas

  • ソフトウェア
  • 人工知能

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