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A network picture has been applied to various physical and biological systems to understand their governing mechanisms intuitively. Utilizing discretization schemes, both electrical and optical materials can also be interpreted as abstract…

Optics · Physics 2016-08-02 Sunkyu Yu , Xianji Piao , Jiho Hong , Namkyoo Park

In this technical note, we study the controllability of diffusively coupled networks from a graph theoretic perspective. We consider leader-follower networks, where the external control inputs are injected to only some of the agents, namely…

Systems and Control · Computer Science 2016-08-17 A. Yasin Yazicioglu , Waseem Abbas , Magnus Egerstedt

We present a general and flexible procedure which allows for the reduction (or expansion) of any dynamical network while preserving the spectrum of the network's adjacency matrix. Computationally, this process is simple and easily…

Dynamical Systems · Mathematics 2010-10-21 L. A. Bunimovich , B. Z. Webb

The resilience of a complex interconnected system concerns the size of the macroscopic functioning node clusters after external perturbations based on a random or designed scheme. For a representation of the interconnected systems with…

Physics and Society · Physics 2017-06-27 Jin-Hua Zhao

Controlling a complex network is of great importance in many applications. The network can be controlled by inputting external control signals through some selected nodes, which are called input nodes. Previous works found that the majority…

Social and Information Networks · Computer Science 2019-10-23 Xizhe Zhang , Qian Li

This paper explores the role of symmetries and reduction in nonlinear control and optimal control systems. The focus of the paper is to give a geometric framework of symmetry reduction of optimal control systems as well as to show how to…

Optimization and Control · Mathematics 2015-02-13 Tomoki Ohsawa

Classical reduced models are low-rank approximations using a fixed basis designed to achieve dimensionality reduction of large-scale systems. In this work, we introduce reduced deep networks, a generalization of classical reduced models…

Numerical Analysis · Mathematics 2020-07-29 Donsub Rim , Luca Venturi , Joan Bruna , Benjamin Peherstorfer

In this era of data deluge, many signal processing and machine learning tasks are faced with high-dimensional datasets, including images, videos, as well as time series generated from social, commercial and brain network interactions. Their…

Machine Learning · Computer Science 2018-03-30 Yanning Shen , Panagiotis A. Traganitis , Georgios B. Giannakis

Despite the significant advances in identifying the driver nodes and energy requiring in network control, a framework that incorporates more complicated dynamics remains challenging. Here, we consider the conformity behavior into network…

Physics and Society · Physics 2022-01-26 Zu-Yu Qian , Cheng Yuan , Jie Zhou , Shi-Ming Chen , Sen Nie

In this paper, we study the following problem: given a connected graph $G$, can we reduce the domination number of $G$ by at least one using $k$ edge contractions, for some fixed integer $k \geq 0$? We present positive and negative results…

Computational Complexity · Computer Science 2019-03-06 Esther Galby , Paloma T. Lima , Bernard Ries

The edge removal problem studies the loss in network coding rates that results when a network communication edge is removed from a given network. It is known, for example, that in networks restricted to linear coding schemes and networks…

Information Theory · Computer Science 2019-07-03 Fei Wei , Michael Langberg , Michelle Effros

In this paper, we show that the minimum number of vertices whose removal disconnects a connected strongly regular graph into non-singleton components, equals the size of the neighborhood of an edge for many graphs. These include blocks…

Combinatorics · Mathematics 2013-11-25 Sebastian M. Cioabă , Jack H. Koolen , Weiqiang Li

Knots are commonly represented and manipulated via diagrams, which are decorated planar graphs. When such a knot diagram has low treewidth, parameterized graph algorithms can be leveraged to ensure the fast computation of many invariants…

Computational Geometry · Computer Science 2023-03-16 Corentin Lunel , Arnaud de Mesmay

Chemical reaction networks (CRNs) are directed graphs with reactant or product complexes as vertices, and reactions as arcs. A CRN is weakly reversible if each of its connected components is strongly connected. Weakly reversible networks…

In recent years, with the increase in renewable energy and storage penetration, power flow studies in low-voltage networks have become of interest in both industry and academia. Many studies use impedance represented by sequence components…

Optimization and Control · Mathematics 2025-06-10 Ching Hong Tam , Frederik Geth , Nadarajah Mithulananthan

We study the problem of interdicting a directed graph by deleting nodes with the goal of minimizing the local edge connectivity of the remaining graph from a given source to a sink. We show hardness of obtaining strictly unicriterion…

Data Structures and Algorithms · Computer Science 2019-11-27 Hassene Aissi , Da Qi Chen , R. Ravi

Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We…

Social and Information Networks · Computer Science 2016-02-24 Jonathan Mellon , Jordan Yoder , Daniel Evans

We analyze the problem of network identifiability with nonlinear functions associated with the edges. We consider a static model for the output of each node and by assuming a perfect identification of the function associated with the…

Optimization and Control · Mathematics 2023-09-14 Renato Vizuete , Julien M. Hendrickx

Random abstract simplicial complex representation provides a mathematical description of wireless networks and their topology. In order to reduce the energy consumption in this type of network, we intend to reduce the number of network…

Probability · Mathematics 2017-09-05 Anaïs Vergne , Laurent Decreusefond , Philippe Martins

Boolean networks have been successfully used in modelling gene regulatory networks. In this paper we propose a reduction method that reduces the complexity of a Boolean network but keeps dynamical properties and topological features and…

Quantitative Methods · Quantitative Biology 2009-07-06 Alan Veliz-Cuba