Design of quantum dot networks for improving prediction performance in reservoir computing
Kazuki Yamanouchi,
Suguru Shimomura,
Jun Tanida
Abstract:A quantum dot (QD) network generates various fluorescence signals based on nonlinear energy dynamics which depend on its structure and composition and is utilized for a component of physical reservoir computing. However, existing designs rely on random QD networks, which is not be optimal for enhancing the prediction performance. In this paper, we propose a method for designing effective quantum dot (QD) networks to improve the performance of reservoir computing. The fluorescence signals from numerous virtual … Show more
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