6 citations · 11 across the 5 of their papers we have counts for
6 papers
Emergence of a stochastic resonance in machine learning
Zheng-Meng Zhai, Ling-Wei Kong, Ying-Cheng Lai
Can noise be beneficial to machine-learning prediction of chaotic systems? Utilizing reservoir computers as a paradigm, we find that injecting noise to the training data can induce…
Digital twins of nonlinear dynamical systems
Ling-Wei Kong, Yang Weng, Bryan Glaz +2
We articulate the design imperatives for machine-learning based digital twins for nonlinear dynamical systems subject to external driving, which can be used to monitor the ``health…
Anticipating synchronization with machine learning
Huawei Fan, Ling-Wei Kong, Ying-Cheng Lai +1
In applications of dynamical systems, situations can arise where it is desired to predict the onset of synchronization as it can lead to characteristic and significant changes in t…
Machine learning prediction of critical transition and system collapse
Ling-Wei Kong, Hua-Wei Fan, Celso Grebogi +1
To predict a critical transition due to parameter drift without relying on model is an outstanding problem in nonlinear dynamics and applied fields. A closely related problem is to…
Synchronization within synchronization: transients and intermittency in ecological networks
Huawei Fan, Ling-Wei Kong, Xingang Wang +2
Transients are fundamental to ecological systems with significant implications to management, conservation, and biological control. We uncover a type of transient synchronization b…
Scaling law of transient lifetime of chimera states under dimension-augmenting perturbations
Ling-Wei Kong, Ying-Cheng Lai
Chimera states arising in the classic Kuramoto system of two-dimensional phase coupled oscillators are transient but they are "long" transients in the sense that the average transi…