Chimeras are this year coming of age since they were first observed by Kuramoto and
Battogtokh in 2002 in a one-dimensional network of complex Ginzburg–Landau equations …

Neuronal networks, similar to many other complex systems, self-organize into fascinating
emergent states that are not only visually compelling, but also vital for the proper functioning …

Random walks are ubiquitous in the sciences, and they are interesting from both theoretical
and practical perspectives. They are one of the most fundamental types of stochastic …

Artificial neural network (ANN) is the backbone of machine learning, specifically deep
learning. The interpolating and learning ability of an ANN makes it an ideal tool for …

Traditionally, much of the study of networks has focused on structural features. Indeed,
mathematical subjects such as graph theory have a rich history of investigating network …

The whale optimization algorithm (WOA) is a nature‐inspired metaheuristic optimization
algorithm, which was proposed by Mirjalili and Lewis in 2016. This algorithm has shown its …

Recent work has shown that machine learning (ML) models can skillfully forecast the
dynamics of unknown chaotic systems. Short-term predictions of the state evolution and long …

Since the concept of discrete memristor was proposed, more and more scholars began to
study this topic. At present, most of works on the discrete memristor are devoted to the …

Dynamical networks are important models for the behaviour of complex systems, modelling
physical, biological and societal systems, including the brain, food webs, epidemic disease …

In the paper, synchronization problem for stochastic neural networks are studied by
impulsively controlling partial states. At each impulsive instant, only part of the states are …