Chaos is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena. Chaos covers a range of topics in the broadly interdisciplinary area of nonlinear science in a manner accessible to researchers from a broad spectrum of disciplines, and publishes special Focus Issues regularly.
Reservoir computing leverages the response of driven dynamic systems for data-driven modeling, time-series prediction, classification, and control. In the past, recurrent neural networks have primarily served as dynamic reservoirs, but…
This Special Topic focuses on topics of complex systems, in particular, we will be interested in Complexity and Machine Learning (ML), from the point of view of physics and mathematics.…
This Special Topic focuses on integrating fundamental processes underlying complex dynamical systems with an emphasis in nonlinear and statistical aspects. The applications range from condensed matter physics, biophysics, and new…