Recurrent self-similarities and machine learning

The inverse problem of building fractals

Timothee Leleu, Akito Sakurai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationMendel
PublisherBrno University of Technology
Pages139-146
Number of pages8
ISBN (Print)9788021438842
Publication statusPublished - 2009
Event15th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2009 - Brno, Czech Republic
Duration: 2009 Jun 242009 Jun 26

Other

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

Fingerprint

Self-similarity
Attractor
Fractal
Machine Learning
Inverse Problem
High-dimensional Data
Decompose
Subset
Similarity

Keywords

  • Data Mining
  • Fractals
  • Inverse problem
  • Iterated Function System
  • Neural Network

Cite this

Leleu, T., & Sakurai, A. (2009). Recurrent self-similarities and machine learning: The inverse problem of building fractals. In Mendel (pp. 139-146). Brno University of Technology.

Recurrent self-similarities and machine learning : The inverse problem of building fractals. / Leleu, Timothee; Sakurai, Akito.

Mendel. Brno University of Technology, 2009. p. 139-146.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Leleu, T & Sakurai, A 2009, Recurrent self-similarities and machine learning: The inverse problem of building fractals. in Mendel. Brno University of Technology, pp. 139-146, 15th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2009, Brno, Czech Republic, 09/6/24.
Leleu T, Sakurai A. Recurrent self-similarities and machine learning: The inverse problem of building fractals. In Mendel. Brno University of Technology. 2009. p. 139-146
Leleu, Timothee ; Sakurai, Akito. / Recurrent self-similarities and machine learning : The inverse problem of building fractals. Mendel. Brno University of Technology, 2009. pp. 139-146
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