Designing Chaotic Attractors: A Semi-supervised Approach

June 27, 2024 ยท Declared Dead ยท ๐Ÿ› Physical Review E

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Authors Tempei Kabayama, Yasuo Kuniyoshi, Kazuyuki Aihara, Kohei Nakajima arXiv ID 2407.09545 Category cs.NE: Neural & Evolutionary Cross-listed cs.LG, math.DS, nlin.CD Citations 7 Venue Physical Review E Last Checked 4 months ago
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 novel semi-supervised framework for designing chaos.
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