Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Barbosa, Wendson A. S."'
Publikováno v:
Nat Commun 15, 3886 (2024)
Machine learning provides a data-driven approach for creating a digital twin of a system - a digital model used to predict the system behavior. Having an accurate digital twin can drive many applications, such as controlling autonomous systems. Often
Externí odkaz:
http://arxiv.org/abs/2406.12876
Publikováno v:
Chaos 34, 023102 (2024)
In this work, we combine nonlinear system control techniques with next-generation reservoir computing, a best-in-class machine learning approach for predicting the behavior of dynamical systems. We demonstrate the performance of the controller in a s
Externí odkaz:
http://arxiv.org/abs/2307.03813
Forecasting the behavior of high-dimensional dynamical systems using machine learning requires efficient methods to learn the underlying physical model. We demonstrate spatiotemporal chaos prediction using a machine learning architecture that, when c
Externí odkaz:
http://arxiv.org/abs/2203.13294
Publikováno v:
Nat Commun 12, 5564 (2021)
Reservoir computing is a best-in-class machine learning algorithm for processing information generated by dynamical systems using observed time-series data. Importantly, it requires very small training data sets, uses linear optimization, and thus re
Externí odkaz:
http://arxiv.org/abs/2106.07688
Autor:
Rowlands, Graham E., Nguyen, Minh-Hai, Ribeill, Guilhem J., Wagner, Andrew P., Govia, Luke C. G., Barbosa, Wendson A. S., Gauthier, Daniel J., Ohki, Thomas A.
The rapidity and low power consumption of superconducting electronics makes them an ideal substrate for physical reservoir computing, which commandeers the computational power inherent to the evolution of a dynamical system for the purposes of perfor
Externí odkaz:
http://arxiv.org/abs/2103.02522
Autor:
Barbosa, Wendson A. S., Griffith, Aaron, Rowlands, Graham E., Govia, Luke C. G., Ribeill, Guilhem J., Nguyen, Minh-Hai, Ohki, Thomas A., Gauthier, Daniel J.
We demonstrate that matching the symmetry properties of a reservoir computer (RC) to the data being processed dramatically increases its processing power. We apply our method to the parity task, a challenging benchmark problem that highlights inversi
Externí odkaz:
http://arxiv.org/abs/2102.00310
We demonstrate experimentally how semiconductor lasers subjected to double optical feedback change the statistics of their chaotic spiking dynamics from Gaussian to long-tail Power Law distributions associated to the emergency of bursting. These chao
Externí odkaz:
http://arxiv.org/abs/1902.03919
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