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Incorporating symmetry as an inductive bias into neural network architecture has led to improvements in generalization, data efficiency, and physical consistency in dynamics modeling. Methods such as CNNs or equivariant neural networks use…

Machine Learning · Computer Science 2022-06-17 Rui Wang , Robin Walters , Rose Yu

The contradiction between the fact that many empirical networks possess power-law degree distribution and the finding that network of heterogeneous degree distribution is difficult to synchronize has been a paradox in the study of network…

Chaotic Dynamics · Physics 2007-05-23 Xingang Wang , Ying-Cheng Lai , Choy Heng Lai

Recently, it has been demonstrated that many large complex networks display a scale-free feature, that is, their connectivity distributions have the power-law form. In this paper, we investigate the synchronization phenomena in a scale-free…

Condensed Matter · Physics 2007-05-23 Xiao Fan Wang , Guanrong Chen

In the freeway network control (FNC) problem, the operation of a traffic network is optimized using only flow control. For special cases of the FNC problem, in particular the case when all merging flows are controlled, there exist tight…

Optimization and Control · Mathematics 2018-03-30 Marius Schmitt , John Lygeros

This paper presents a framework for the study of convergence when the nodes' dynamics may be both piecewise smooth and/or nonidentical across the network. Specifically, we derive sufficient conditions for global convergence of all node…

Dynamical Systems · Mathematics 2014-04-08 Pietro DeLellis , Mario di Bernardo , Davide Liuzza

We consider the freeway network control problem where the aim is to optimize the operation of traffic networks modeled by the Cell Transmission Model via ramp metering and partial mainline demand control. Optimal control problems using the…

Optimization and Control · Mathematics 2018-05-28 Marius Schmitt , John Lygeros

This paper discusses the controllability problem of complex networks. It is shown that almost any weighted complex network with noise on the strength of communication links is controllable in the sense of Kalman controllability. The concept…

Systems and Control · Computer Science 2018-05-07 Ning Cai , Ming He , Qiu-Xuan Wu , M. Junaid Khan

In this paper, the complete synchronization problem of linearly coupled neural networks with reaction-diffusion terms and time-varying delays via aperiodically intermittent pinning control is investigated. The coupling matrix for the…

Systems and Control · Computer Science 2016-04-13 Xiwei Liu , Zhang Chen , Lingjun Zhou

We study the synchronizability and the synchronization dynamics of networks of nonlinear oscillators. We investigate how the synchronization of the network is influenced by some of its topological features such as variations of the power…

Disordered Systems and Neural Networks · Physics 2007-12-08 Mario di Bernardo , Franco Garofalo , Francesco Sorrentino

As a quantification of the main bottleneck to flow over a graph, the network property of conductance plays an important role in the process of synchronization of network-coupled dynamical systems. Diffusive coupling terms serve not only to…

Physics and Society · Physics 2025-10-29 C. Tyler Diggans

In many real-world networks the ability to synchronize is a key property for its performance. Examples include power-grid, sensor, and neuron networks as well as consensus formation. Recent work on undirected networks with diffusive…

Dynamical Systems · Mathematics 2014-08-21 Jan Philipp Pade , Tiago Pereira

Neural networks can synchronize by learning from each other. In the case of discrete weights full synchronization is achieved in a finite number of steps. Additional networks can be trained by using the inputs and outputs generated during…

Disordered Systems and Neural Networks · Physics 2007-11-16 Andreas Ruttor

Synchronization is of central importance in power distribution, telecommunication, neuronal, and biological networks. Many networks are observed to produce patterns of synchronized clusters, but it has been difficult to predict these…

We study the effects of nonzero time delays in stochastic synchronization problems with linear couplings in complex networks. We consider two types of time delays: transmission delays between interacting nodes and local delays at each node…

Statistical Mechanics · Physics 2012-12-03 D. Hunt , B. K. Szymanski , G. Korniss

We investigate robustness of deep feed-forward neural networks when input data are subject to random uncertainties. More specifically, we consider regularization of the network by its Lipschitz constant and emphasize its role. We highlight…

Machine Learning · Computer Science 2019-04-15 Nicolas Couellan

The propensity for synchronization is studied in a complex network of asymmetrically coupled units, where the asymmetry in a given link is determined by the relative age of the involved nodes. In growing scale-free networks synchronization…

Disordered Systems and Neural Networks · Physics 2007-05-23 Dong-Uk Hwang , Mario Chavez , Andreas Amann , Stefano Boccaletti

This work is concerned with the design and effects of the synchronization gains on the synchronization problem for a class of networked distributed parameter systems. The networked systems, assumed to be described by the same evolution…

Optimization and Control · Mathematics 2013-06-03 Michael A. Demetriou

This paper considers the cluster synchronization problem of generic linear dynamical systems whose system models are distinct in different clusters. These nonidentical linear models render control design and coupling conditions highly…

Systems and Control · Electrical Eng. & Systems 2021-11-05 Zhongchang Liu , Wing Shing Wong , Hui Cheng

In the past few years, the discoveries of small-world and scale-free properties of many natural and artificial complex networks have stimulated significant advances in better understanding the relationship between the topology and the…

Disordered Systems and Neural Networks · Physics 2009-09-29 Xiang Li

Synchrony is one of the most common dynamical states emerging on networks. The speed of convergence towards synchrony provides a fundamental collective time scale for synchronizing systems. Here we study the asymptotic synchronization times…

Disordered Systems and Neural Networks · Physics 2015-06-30 Carsten Grabow , Stefan Grosskinsky , Marc Timme