Dynamical systems theory has long provided a foundation for understanding evolving phenomena across scientific domains. Yet, the application of this theory to complex real-world systems remains ...

We often encounter nonlinear dynamical systems that behave unpredictably, such as the Earth's climate and the stock market. To analyze them, measurements taken over time are used to reconstruct the ...

Nonlinear dynamical systems are systems that can undergo sudden shifts not due to changes in their state or stability, but in response to the rate at which external conditions or parameters change.

There has been tremendous development in linear controllability of complex networks. Real-world systems are fundamentally nonlinear. Is linear controllability relevant to nonlinear dynamical networks?

Engineers at Tokyo Institute of Technology (Tokyo Tech) have demonstrated a simple computational approach for supporting the classification performance of neural networks operating on sensor time ...