Dynamical process of learning chaotic time series by neural networks

Tsuyoshi Hondou, Yasuji Sawada

研究成果: Conference contribution

抄録

We report the result of computer simulations on the learning process of temporal series by artificial neural networks. In our simulation, we used a feedforward neural network model with 4-layers to study the capability and dynamical learning process of chaotic time series produced by triangular (tent) maps. We found a critical time (tcr) at which learning process proceeds abruptly. We also found that the critical time (tcr) is shorter, the larger is the initial deviation from the target of learning. We tried detailed discussion about the learning process to explain these interesting phenomena, and new order parameter coherency is introduced to characterize these processes.

本文言語English
ホスト出版物のタイトルProceedings of the International Joint Conference on Neural Networks
出版社Publ by IEEE
ページ2387-2390
ページ数4
ISBN(印刷版)0780314212, 9780780314214
出版ステータスPublished - 1993 12月 1
イベントProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) - Nagoya, Jpn
継続期間: 1993 10月 251993 10月 29

出版物シリーズ

名前Proceedings of the International Joint Conference on Neural Networks
3

Other

OtherProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3)
CityNagoya, Jpn
Period93/10/2593/10/29

ASJC Scopus subject areas

  • ソフトウェア
  • 人工知能

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