Designing chaotic attractors: A semisupervised approach

Chaotic dynamics are ubiquitous in nature and useful in engineering, but their geometric design can be challenging. Here we propose a method using reservoir computing to generate chaos with a desired shape by providing a periodic orbit as a template, called a skeleton. We exploit a bifurcation of the reservoir to intentionally induce unsuccessful training of the skeleton, revealing inherent chaos. The emergence of this untrained attractor, resulting from the interaction between the skeleton and the reservoir's intrinsic dynamics, offers a semisupervised framework for designing chaos.

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Publication Details

Journal
Physical review. E
Published
2025-03-11
DOI
https://doi.org/10.1103/physreve.111.034207
Citations
6
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
14.89

Funders

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article

Designing chaotic attractors: A semisupervised approach

Yasuo Kuniyoshi, Kazuyuki Aihara, Kohei Nakajima, Tempei Kabayama
6 citations
Physical review. E
Neural Networks and Reservoir Computing
14.89
article

Designing chaotic attractors: A semisupervised approach

Yasuo Kuniyoshi, Kazuyuki Aihara, Kohei Nakajima, Tempei Kabayama
article en
6 citations

Abstract

Chaotic dynamics are ubiquitous in nature and useful in engineering, but their geometric design can be challenging. Here we propose a method using reservoir computing to generate chaos with a desired shape by providing a periodic orbit as a template, called a skeleton. We exploit a bifurcation of the reservoir to intentionally induce unsuccessful training of the skeleton, revealing inherent chaos. The emergence of this untrained attractor, resulting from the interaction between the skeleton and the reservoir's intrinsic dynamics, offers a semisupervised framework for designing chaos.

Physical review. EVol. 111(3)
The University of Tokyo (JP)
Japan Society for the Promotion of Science, Japan Science and Technology Agency
Openalex Percentile: Top 1%
Neural Networks and Reservoir Computing
14.89
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