The dynamical systems found in nature are rarely isolated. Instead they interact and
influence each other. The coupling functions that connect them contain detailed information …

The concept of reservoir computing emerged from a specific machine learning paradigm
characterized by a three-layered architecture (input, reservoir, and output), where only the …

Noise and time-delays are ubiquitous in physical and biological systems. In this paper, the
multiple time-delays coupled FitzHugh-Nagumo (FHN) models is employed to investigate …

A “chimera state” is a dynamical pattern that occurs in a network of coupled identical
oscillators when the symmetry of the oscillator population is broken into synchronous and …

In realistic systems of coupled oscillators, it is desired to predict the onset of synchronization
where the system equations are unknown, raising the need to develop a prediction …

We devise a machine learning technique to solve the general problem of inferring network
links that have time delays using only time series data of the network nodal states. This task …

Topology identification of complex networks is an important and meaningful research
direction. In recent years, the topology identification method based on adaptive …

This article deals with the spectra of Laplacians of weighted graphs. In this context, two
objects are of fundamental importance for the dynamics of complex networks: the second …

In this paper, we investigated the possibility of using the magnetic Laplacian to characterize
directed networks. We address the problem of characterization of network models and …

The relation between network structure and dynamics is determinant for the behavior of
complex systems in numerous domains. An important long-standing problem concerns the …