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Neural networks with a large number of parameters admit a mean-field description, which has recently served as a theoretical explanation for the favorable training properties of "overparameterized" models. In this regime, gradient descent…

Machine Learning · Statistics 2019-03-28 Grant Rotskoff , Samy Jelassi , Joan Bruna , Eric Vanden-Eijnden

We analyze the interplay of synchronization and structure evolution in an evolving network of phase oscillators. An initially random network is adaptively rewired according to the dynamical coherence of the oscillators, in order to enhance…

Statistical Mechanics · Physics 2007-09-27 Pablo M. Gleiser , Damián H. Zanette

Heterogeneity in the degree distribution is known to suppress global synchronization in complex networks of symmetrically coupled oscillators. Scale-free networks display a great deal of heterogeneity, containing a few nodes, termed hubs,…

Chaotic Dynamics · Physics 2010-10-11 Tiago Pereira

Fast cortical rhythms with stochastic and intermittent neural discharges have been observed in electric recordings of brain activity. Recently, Brunel et al. developed a framework to describe this kind of fast sparse synchronization in both…

Neurons and Cognition · Quantitative Biology 2014-09-03 Sang-Yoon Kim , Woochang Lim

We study the generalized synchronization and its stability using master stability function (MSF), in a network of coupled nearly identical dynamical systems. We extend the MSF approach for the case of degenerate eigenvalues of the coupling…

Chaotic Dynamics · Physics 2015-11-11 Suman Acharyya , R. E. Amritkar

From the flashes of fireflies to Josephson junctions and power infrastructure, networks of coupled phase oscillators provide a powerful framework to describe synchronization phenomena in many natural and engineered systems. Most real-world…

Adaptation and Self-Organizing Systems · Physics 2022-03-02 Sherwood Martineau , Tim Saffold , Timothy T. Chang , Henrik Ronellenfitsch

In a generalized framework, where multi-state and inter-state linkages are allowed, we derive a sufficient condition for the stability of synchronization in a network of chaotic attractors. This condition explicitly relates the network…

Chaotic Dynamics · Physics 2014-07-29 Saeed Manaffam , Alireza Seyedi

Asynchronous computation and gradient compression have emerged as two key techniques for achieving scalability in distributed optimization for large-scale machine learning. This paper presents a unified analysis framework for distributed…

Optimization and Control · Mathematics 2018-11-30 Sarit Khirirat , Hamid Reza Feyzmahdavian , Mikael Johansson

The issue of synchronization in the power grid is receiving renewed attention, as new energy sources with different dynamics enter the picture. Global metrics have been proposed to evaluate performance and analyzed under highly simplified…

Systems and Control · Computer Science 2019-05-20 Fernando Paganini , Enrique Mallada

Many real-world networks have properties of small-world networks, with clustered local neighborhoods and low average-shortest path (ASP). They may also show a scale-free degree distribution, which can be generated by growth and preferential…

Statistical Mechanics · Physics 2007-05-23 Marcus Kaiser , Claus C. Hilgetag

We explore linear control of the one-dimensional non-linear Kardar--Parisi--Zhang (KPZ) equation with the goal to understand the effects the control process has on the dynamics and on the stationary state of the resulting stochastic growth…

Statistical Mechanics · Physics 2021-05-11 Priyanka , Uwe C Tauber , Michel Pleimling

Most real-world networks are endowed with the small-world property, by means of which the maximal distance between any two of their nodes scales logarithmically rather than linearly with their size. The evidence sparkled a wealth of studies…

Physics and Society · Physics 2023-04-21 Tanu Raghav , Stefano Boccaletti , Sarika Jalan

In a first step towards the comprehension of neural activity, one should focus on the stability of the various dynamical states. Even the characterization of idealized regimes, such as a perfectly periodic spiking activity, reveals…

Disordered Systems and Neural Networks · Physics 2014-09-08 Simona Olmi , Antonio Politi , Alessandro Torcini

We study synchronization in scalar nonlinear systems connected over a linear network with stochastic uncertainty in their interactions. We provide a sufficient condition for the synchronization of such network systems expressed in terms of…

Optimization and Control · Mathematics 2017-02-20 Amit Diwadkar , Umesh Vaidya

In this manuscript, we study the problem of robust synchronization in networks of diffusively time-delayed coupled nonlinear systems. In particular, we prove that, under some mild conditions on the input-output dynamics of the systems and…

Systems and Control · Computer Science 2017-11-01 Carlos Murguia , Henk Nijmeijer , Justin Ruths

Today's mainstream network timing models for distributed computing are synchrony, partial synchrony, and asynchrony. These models are coarse-grained and often make either too strong or too weak assumptions about the network. This paper…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-29 Neil Giridharan , Ittai Abraham , Natacha Crooks , Kartik Nayak , Ling Ren

By a small-size complex network of coupled chaotic Hindmarsh-Rose circuits, we study experimentally the stability of network synchronization to the removal of shortcut links. It is shown that the removal of a single shortcut link may…

Chaotic Dynamics · Physics 2018-04-04 Ben Cao , Yafeng Wang , Liang Wang , Yizhen Yu , Xingang Wang

The cooperative behavior of neurons and neuronal areas associated with the synchronization behavior proves to be a fundamental neural mechanism. In addition, abnormal levels of synchronization have been related to unhealthy neural…

Biological Physics · Physics 2023-11-16 Bruno R. R. Boaretto

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

Many image processing tasks involve image-to-image mapping, which can be addressed well by fully convolutional networks (FCN) without any heavy preprocessing. Although empirically designing and training FCNs can achieve satisfactory…

Machine Learning · Computer Science 2019-01-25 Jianjie Lu , Kai-yu Tong