Recurrent self-similarities and machine learning: The inverse problem of building fractals

Timothee Leleu, Akito Sakurai

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

A method to analyse recurrent similarities, or self-similarities, in higher dimensional data set, is proposed in this paper. An algorithm capable of solving the inverse problem of building a fractal is detailed. The latter is constituted of three parts: the decomposition of the data into subsets; the determination of a simple IFS from these sets; the reconstruction of the attractor. Basic attractors of fractals are reconstructed using these IFS, with a small error.

本文言語English
ホスト出版物のタイトルMendel
編集者Matousek Radek
出版社Brno University of Technology
ページ139-146
ページ数8
ISBN(電子版)9788021438842
出版ステータスPublished - 2009 1 1
イベント15th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2009 - Brno, Czech Republic
継続期間: 2009 6 242009 6 26

出版物シリーズ

名前Mendel
ISSN(印刷版)1803-3814

Other

Other15th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2009
国/地域Czech Republic
CityBrno
Period09/6/2409/6/26

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)
  • 計算数学

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