Article
Physics, Multidisciplinary
Yanik-Pascal Forster, Luca Gamberi, Evan Tzanis, Pierpaolo Vivo, Alessia Annibale
Summary: In this study, a novel method is proposed for calculating mean first-passage times (MFPTs) for random walks on graphs using dimensionality reduction technique. The method preserves the MFPTs between certain nodes and provides explicit formulae for MFPTs in specific graph structures. For other types of graphs, the generalized approximation method gives useful results.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2022)
Article
Physics, Fluids & Plasmas
Feng Huang, Hanshuang Chen
Summary: This study investigates discrete-time random walks with first-passage resetting processes on arbitrary networks, deriving exact expressions for stationary occupation probability, average number of resets, and mean first-passage time. Results show that these quantities can be expressed in terms of the fundamental matrix, demonstrating the advantage of first-passage resetting in global search on various networks.
Article
Physics, Multidisciplinary
Xiaomin Wang, Jing Su, Fei Ma, Bing Yao
Summary: In this paper, we generated a scale-free network using a rectangle operation and studied its topological structures, as well as characteristic quantities related to the network. These characteristic quantities can be used to evaluate network properties and have significant applications in science and engineering.
FRONTIERS IN PHYSICS
(2021)
Article
Physics, Multidisciplinary
M. Dahlenburg, G. Pagnini
Summary: We study the mean first-passage time (MFPT) for asymmetric continuous-time random walks characterized by waiting-times with finite mean and jump-sizes with finite mean and variance. We derive a nonhomogeneous Wiener-Hopf integral equation that allows for the exact calculation of the MFPT, which depends on the distribution of jump-sizes and the mean-value of waiting-times. Through a case study, we show that the MFPT is independent of the jump-sizes distribution in the opposite direction to the boundary and depends on the specific distribution of jump-sizes for starting points near the boundary.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2022)
Article
Mathematics, Interdisciplinary Applications
Long Gao, Junhao Peng, Chunming Tang
Summary: The study focused on the first-passage process on fractal scale-free trees, examining the impact of the time to reach the target site on network transport efficiency. By introducing proper weights and the parameter w, the process was accelerated, and a method to find the minimum GMFPT was presented.
FRACTAL AND FRACTIONAL
(2021)
Article
Physics, Multidisciplinary
Hanshuang Chen, Guofeng Li, Feng Huang
Summary: This paper investigates the effect of stochastic resetting on the first passage properties of discrete-time absorbing Markov chains. The authors derive the mean first passage time and splitting probabilities using a renewal approach. They also present a sufficient condition for optimizing the mean first passage time and apply their results to two specific examples.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2022)
Article
Physics, Fluids & Plasmas
Fei Ma, Ping Wang
Summary: The study proposes a simple algorithmic framework for generating power-law graphs with small diameters and examines their structural properties. The results show that these graphs have unique features such as density characteristics and higher trapping efficiency compared to existing scale-free models, confirmed through extensive simulations.
Article
Computer Science, Artificial Intelligence
Fei Ma, Ping Wang, Xudong Luo, Renbo Zhu
Summary: In this article, a principled framework using Vertex-based and Edge-based uniform generation mechanisms for stochastic uniform growth tree networks is proposed. The associated structural features are analytically uncovered. The framework includes three different forms of vertex-degree distribution and three distinct structural shapes observed in the study of fractal phenomena. The analytical solution to fractal dimension for fractal structure is obtained, and well-known models such as Vicsek fractal and T-graph fall into the framework. Two families of stochastic uniform growth tree networks generated through the framework are precisely considered, and the impact of randomness on the efficiency of delivering information is analyzed.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Physics, Multidisciplinary
A. Barbier-Chebbah, O. Benichou, R. Voituriez
Summary: Self-interacting random walks with long-range memory effects have significant consequences on exploration properties. Attractive self-interactions provide advantages for local space exploration, while repulsive self-interactions accelerate global exploration.
Article
Mathematics, Applied
Shahid Zaman, Asad Ullah
Summary: This paper investigates the random walks of octagonal cell network by using the Laplacian spectrum method. The mean first passage time (τ) and Kemeny's constant (Ω) between nodes are obtained. The mean first passage time (τ) is explicitly studied in terms of the eigenvalues of a Laplacian matrix, while Kemeny's constant (Ω) is introduced to measure node strength and determine the scaling of the random walks. An explicit expression of Kemeny's constant and mean first passage time for octagonal cell network is provided based on Laplacian eigenvalues and the correlation among roots of characteristic polynomial. Comparative studies are also performed for τ and Ω based on the achieved results. This work also delivers an inclusive approach for exploring random walks of networks, particularly biased random walks, which can help better understand and tackle practical problems such as search and routing on networks.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Physics, Fluids & Plasmas
Hanshuang Chen, Yanfei Ye
Summary: This study investigates discrete-time random walks on networks subject to time-dependent stochastic resetting. The results demonstrate that time-modulated resetting protocols can be more advantageous in accelerating the completion of a target search process compared to constant-probability resetting.
Article
Multidisciplinary Sciences
Alexandre Bovet, Jean-Charles Delvenne, Renaud Lambiotte
Summary: This article introduces a method based on a dynamical process evolving on a temporal network, which uncovers different dynamic scales in a system by considering the ordering of edges in forward and backward time. The method provides a new approach to extracting a simplified view of time-dependent network interactions in a system.
Article
Mathematics, Applied
Junhao Peng, Trifce Sandev, Ljupco Kocarev
Summary: This work examines the survival probabilities and first encounter time of fixed and mobile targets on different structures, revealing variations in survival strategies among different structures.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2021)
Article
Physics, Multidisciplinary
Yan Wang, Xinxin Ca, Tongfeng Weng, Huijie Yang, Changgui Gu
Summary: In this study, we introduced lowest-degree preference random walks on complex networks, which significantly reduced search time compared to random walks on the majority of real networks. The optimal tuning parameter showed a strong positive correlation with entropy of degree sequence, indicating how much the search time could be reduced. This work opens up a new path for designing efficient search strategies with only local information available.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Physics, Fluids & Plasmas
Gennaro Tucci, Andrea Gambassi, Satya N. Majumdar, Gregory Schehr
Summary: This study investigates the statistical properties of a single run-and-tumble particle (RTP) reaching a fixed target, with or without resetting, in one spatial dimension. By analyzing the first-passage time distribution of a free RTP and introducing resetting, the research reveals interesting singular behaviors and rich phase diagrams in the (b, v) plane, providing important insights into the behavior of RTP under different conditions.
Article
Automation & Control Systems
Xiaoling Wang, Housheng Su, Fan Zhang, Guanrong Chen
Summary: This article investigates the state estimation problem of a continuous-time linear time-invariant system in the presence of unknown external disturbance and measurement noise. A robust distributed interval observer is designed, which consists of a group of sensors communicating through a directed graph. The communication, heterogeneity, and undetectability of the sensors impose stringent requirements on the observer construction. To address these restrictions, an internally positive representation from a single agent system is introduced. Numerical simulations are conducted to validate the theoretical results.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Xu Zhang, Guanrong Chen
Summary: A new geometric criterion is developed to determine the existence of chaos in continuous-time autonomous systems in three-dimensional Euclidean spaces. This criterion differs from traditional methods as it does not rely on equilibrium points or the condition of transversal homoclinic or heteroclinic orbit of a Poincare map.
JOURNAL OF DYNAMICAL AND CONTROL SYSTEMS
(2023)
Article
Automation & Control Systems
Yuqing Hao, Qingyun Wang, Zhisheng Duan, Guanrong Chen
Summary: In this article, the discernibility of topological variations for networked linear time-invariant (LTI) systems is investigated. A necessary and sufficient condition is derived, revealing the impact of topological variations, node-system dynamics, and inner interactions on network discernibility. The condition presented is more general than existing conditions. Furthermore, the discernibility of topological variations for multiagent systems is revisited, and a new necessary and sufficient condition is established with broader applicability.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Yang Lou, Lin Wang, Shengli Xie, Guanrong Chen
Summary: This paper proposes a hybrid approximation method to estimate the controllability robustness performance of large-scale directed random-graph networks under random edge-removal attacks. Two threshold values are set to classify general random-graph networks as 'dense', 'sparse', or 'median', according to the average degree. Simulation results verify that the proposed method can accurately approximate the controllability curves and is more time-efficient compared to conventional attack simulations.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Yang Lou, Ruizi Wu, Junli Li, Lin Wang, Chang-Bing Tang, Guanrong Chen
Summary: This study proposes an efficient robustness predictor based on multiple convolutional neural networks (mCNN-RP) for predicting the network connectivity robustness. By classifying and estimating networks, it can accurately predict the connectivity robustness of different complex networks and outperforms existing prediction measures.
Article
Automation & Control Systems
Yong Wang, Zhuo Liu, Leo Yu Zhang, Fabio Pareschi, Gianluca Setti, Guanrong Chen
Summary: This article performs a theoretical study on pseudorandom number generation using the well-studied 2-D coupled map lattice (2D CML). It proposes a method to extract uniformly distributed independent bits from the system orbits and demonstrates its effectiveness through simulation experiments.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Physics, Multidisciplinary
Jiashuo Sun, Linying Xiang, Guanrong Chen
Summary: In this article, the dynamical robustness of a directed complex network with additive noise is studied. The failure of a node in the network is modeled by injecting noise into the node. A new robustness metric is formulated to characterize the synchronization of the network to the additive noise under the framework of mean-square stochastic stability. It is found that the node dynamics plays a crucial role in the dynamical robustness of the directed network. Numerical simulations are provided for illustration and verification.
FRONTIERS IN PHYSICS
(2023)
Article
Automation & Control Systems
Bing Mao, Xiaoqun Wu, Jinhu Lu, Guanrong Chen
Summary: This article investigates the uniformly predefined-time bounded consensus of leader-following multiagent systems with unknown system nonlinearity and external disturbance. Distributed adaptive fuzzy control is used to analyze and design the system, achieving global consensus within a predefined time.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Jie-Ning Wu, Xiang Li, Guanrong Chen
Summary: This article examines the controllability of multi-input/multi-output linear time-invariant systems in a snapback interlayer coupling framework. It establishes necessary and sufficient conditions for the controllability of three-layer snapback networks and obtains controllability conditions for the superposition of these networks. These conditions are related to smaller scale factor networks and illustrate the impact of interlayer coupling frameworks, intralayer network topologies, node dynamics, inner interactions, and external control inputs on the controllability of snapback networks. The controllability conditions of three-layer snapback networks are also extended to the M-layer setting. Several examples are provided to illustrate the effectiveness of these controllability conditions.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2023)
Article
Mathematics
Jiali Wang, Changbing Tang, Jianquan Lu, Guanrong Chen
Summary: In this paper, a decision optimization method based on zero-determinant (ZD) strategies is proposed to help workers in a crowdsourcing system make optimal decisions under incomplete information. The problem is formulated as an iterated game with incomplete information, and the optimal decision of workers in terms of ZD strategies is analyzed. Numerical simulations are conducted to demonstrate the performances of different strategies and the impact of parameters on the payoffs of workers.
Article
Automation & Control Systems
Wenbo Hu, Fei Chen, Linying Xiang, Guanrong Chen
Summary: This article studies coordinated tracking of underactuated and uncertain autonomous surface vehicles (ASVs) via model-reference reinforcement learning control. It is demonstrated that the proposed algorithm has a better performance over baseline control and effectively improves the training efficiency over reinforcement learning.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Zhen Liu, Liangguang Pan, Guanrong Chen
Summary: In this article, a computational model called link-information augmented twin autoencoders is proposed to remove noisy links from observed network and recover the real network. Extensive experiments show that the proposed model outperforms other methods in network denoising and provides interpretable evidence to support its superiority.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Mathematics, Interdisciplinary Applications
Yuqian Zhou, Guanrong Chen, Jibin Li
Summary: By applying the techniques from dynamical systems and singular traveling wave theory developed by Li and Chen [2007] to analyze the traveling wave system of the cubic Camassa-Holm type equation, it has been discovered that the bifurcation portraits of this equation exhibit all possible exact explicit bounded solutions (solitary wave solutions, periodic wave solutions, peakon as well as periodic peakons) under different parameter conditions. A total of 19 explicit exact parametric representations of the traveling wave system of the Camassa-Holm type equation are provided.
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
(2023)
Article
Computer Science, Artificial Intelligence
Jiajun Zhou, Zhi Chen, Min Du, Lihong Chen, Shanqing Yu, Guanrong Chen, Qi Xuan
Summary: In this paper, robust community detection methods are proposed to improve the performance and robustness of community detection for real-world networks. By enhancing network structure through two generic algorithms, significant performance improvement is achieved for representative community detection algorithms. Additionally, the new methods also optimize the network structure and enhance robustness against adversarial attack.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Mathematics, Applied
Zhensu Wen, Guanrong Chen
Summary: This paper uses the methodology of dynamical systems and singular traveling wave theory to prove the existence of all possible bounded solutions of the traveling wave system in the Hertz chain model under different parameter conditions. Furthermore, it obtains 23 exact explicit parametric representations for various types of traveling wave systems.
DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES S
(2023)
