Article
Physics, Fluids & Plasmas
Can Xu, Xin Jin, Yonggang Wu
Summary: The coupled phase oscillator model is widely used to understand collective dynamics in large ensembles of interacting units. This study investigates the impacts of heterogeneous strategies, correlation function, and natural frequency distribution on emergent dynamics using a variant of the Kuramoto model. An analytical treatment is developed to capture the essential properties of the equilibrium states.
Article
Chemistry, Analytical
Xiufeng Guo, Pengchun Rao, Zhaoyan Wu
Summary: This paper investigates the fixed-time synchronization problem of a Kuramoto-oscillator network in the presence of a pacemaker. The synchronization criteria for phase agreement and frequency synchronization are presented using distributed control strategies and Lyapunov stability analysis. The upper bounds of synchronization time are obtained, and numerical simulations confirm the effectiveness of the derived results.
Article
Physics, Fluids & Plasmas
Ajay Deep Kachhvah, Sarika Jalan
Summary: The study found that in multilayer and multiplexed networks, a multilayer network constructed by setting up all-to-all interlayer connections can lead to explosive synchronization in the two populations, while a multiplex formation with only mirror nodes interconnected supports simultaneous explosive transitions in the two populations. Both explosive synchronization and chimera phenomena are supported by rigorous theoretical mean-field analysis in the presence of random pinning in interlayer interactions.
Article
Physics, Multidisciplinary
Pengchun Rao, Xiufeng Guo
Summary: This paper studies the finite-time synchronization problem of a Kuramoto-oscillator network with a pacemaker. By constructing a cyber-physical system (CPS), the finite-time phase agreement and frequency synchronization of the network are explored for identical and non-identical oscillators, respectively. Sufficient conditions are deduced for ensuring the phase agreement and frequency synchronization for arbitrary initial phases and/or frequencies under distributed strategies, and upper bound estimations of convergence time are obtained accordingly.
FRONTIERS IN PHYSICS
(2022)
Article
Automation & Control Systems
S. Emre Tuna
Summary: The synchronization of identical harmonic oscillators interconnected via various couplings is studied, with a focus on constructing a complex Laplacian matrix for overall coupling. The oscillators asymptotically synchronize when the matrix has a single eigenvalue on the imaginary axis. This result generalizes some known spectral tests for synchronization, and simpler Laplacian constructions can also work under certain structural conditions.
Article
Physics, Fluids & Plasmas
M. Manoranjani, R. Gopal, D. Senthilkumar, V. K. Chandrasekar, M. Lakshmanan
Summary: In this study, we investigate the phase diagram of the Sakaguchi-Kuramoto model, including both higher-order interactions and traditional pairwise interactions. By introducing asymmetry parameters and examining different frequency distributions, we analyze the collective dynamics and transitions in the phase diagrams. The results demonstrate that higher-order coupling leads to the spread of bistable regions and the manifestation of bistability between incoherent and partially synchronized states, even with unimodal frequency distribution. The asymmetry parameters facilitate the emergence of multiple bistable regions in the phase diagrams, and larger values of the asymmetry parameters result in only monostable dynamical states in the phase diagrams.
Article
Mathematics, Interdisciplinary Applications
Pitambar Khanra, Pinaki Pal
Summary: This study proposes an adaptive master-slave coupling scheme to achieve explosive synchronization in a targeted layer of a multilayer network. The proposed scheme can induce ES in the slave layer even with a very small percentage of nodes receiving feedback from the master layer. Additionally, tuning a parameter in the adaptive coupling function of the master layer can amplify the hysteresis width in the slave layer in the ES regime.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Mathematics, Applied
Can Xu, Yonggang Wu, Zhigang Zheng, Longkun Tang
Summary: We consider a variant of the mean-field model of coupled phase oscillators with uniform distribution of natural frequencies. By establishing correlations between the quenched disorder of intrinsic frequencies and coupling strength with both in- and out-coupling heterogeneities, we reveal a generic criterion for the onset of partial locking that takes place in a domain with the coexistence of phase-locked oscillators and drifters. Our research could find applicability in better understanding the phase transitions and related collective phenomena involving synchronization control in networked systems.
Article
Mathematics, Applied
Hyunsuk Hong, Erik A. Martens
Summary: This study investigated the phase coherence dynamics in coupled oscillators based on the correlation between frequencies and coupling strengths. Results showed that in the case of correlated disorder, the oscillator population splits into two subpopulations, while in the uncorrelated case, it may split into four phase-locked subpopulations, leading to periodic global synchronization motion. In both cases of disorder, an incoherent state exists, with instability observed in the correlated case and neutral stability in the uncorrelated case.
Article
Mathematics
Dharma Raj Khatiwada
Summary: This paper investigates the synchronization of a finite number of oscillators in the presence of external perturbations. The results show that synchronization persists even under the influence of external factors, and occasional boosting of the coupling strength is enough to maintain the assembly of oscillators in a synchronized state persistently.
Article
Multidisciplinary Sciences
Caique C. Rodrigues, Caue M. Kersul, Andre G. Primo, Michal Lipson, Thiago P. Mayer Alegre, Gustavo S. Wiederhecker
Summary: Experimental exploration of synchronization in scalable oscillator microsystems has provided deeper understanding of networks, collective phenomena, and signal processing. The demonstration of entrainment and frequency division in optomechanical oscillators opens up possibilities for frequency synthesizers and nonlinear sensing applications.
NATURE COMMUNICATIONS
(2021)
Article
Automation & Control Systems
Petro Feketa, Alexander Schaum, Thomas Meurer
Summary: In this study, we have proven the existence of a multidimensional nontrivial invariant toroidal manifold for the Kuramoto network with adaptive coupling, which corresponds to the multicluster behavior of oscillator phases. By analyzing the adaptive coupling strengths, we derived sufficient conditions and examined the robustness of the invariant manifold with respect to perturbations in the network structure. Additionally, we showcased the application of these results in interconnection topology design for inducing desired multicluster behavior in the network.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Physics, Fluids & Plasmas
Can Xu, Xuan Wang, Zhigang Zheng, Zongkai Cai
Summary: The study introduces a general framework for analyzing the stability and bifurcation of collective dynamics in oscillator populations by extending global coupling dependent on an arbitrary function of the Kuramoto order parameter. It reveals that all steady states characterizing the long-term macroscopic dynamics can be expressed in a universal profile based on frequency-dependent Ott-Antonsen reduction. Furthermore, it uncovers the equivalence between the empirical stability criterion for each steady state in the system and its linear stability condition determined by nontrivial eigenvalues.
Article
Mathematics, Applied
Zongkai Cai, Zhigang Zheng, Can Xu
Summary: This study investigates a variant of the Kuramoto model, revealing the existence of partial locking when introducing a power law function with exponent less than 1, and the absence of such phenomenon when the exponent is greater than or equal to 1. Through a specific assumption, the long-term macroscopic dynamics and corresponding critical properties of the model can be analytically described, while constructing a characteristic function to provide intuitive interpretation of the dynamic phenomena in the system.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2022)
Article
Physics, Fluids & Plasmas
Pragjyotish Bhuyan Gogoi, Suresh Kumarasamy, Awadhesh Prasad, Ram Ramaswamy
Summary: Phase slips are common in coupled oscillator systems, characterized by abrupt changes in phase difference during the route to phase synchrony. Previous analysis relied on identifying remnants of saddle-nodes or ghosts, but our study offers a more precise description by examining the dynamics in detail. Phase shifts and locks occur at stationary points of phase velocities in phase oscillators, and in networks of coupled oscillators, phase slips between pairs of oscillators do not occur simultaneously in general. We also explore different systems that exhibit phase synchrony.
Article
Automation & Control Systems
Yi-Qing Zhang, Xiang Li, Athanasios V. Vasilakos
IEEE TRANSACTIONS ON CYBERNETICS
(2020)
Article
Engineering, Electrical & Electronic
Pengchun Rao, Xiang Li
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2020)
Article
Mathematics, Applied
Chuang Ma, Han-Shuang Chen, Xiang Li, Ying-Cheng Lai, Hai-Feng Zhang
SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS
(2020)
Article
Engineering, Electrical & Electronic
Huiyan Li, Xiang Li
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2020)
Article
Physics, Condensed Matter
Xiao-Jie Li, Xiang Li
EUROPEAN PHYSICAL JOURNAL B
(2020)
Article
Computer Science, Artificial Intelligence
Grzegorz Surowka, Maciej Ogorzalek
Summary: Proper diagnosis of cutaneous melanoma is crucial and efficient wavelet-based features can serve as signals of neoplastic changes. Classification performance strongly depends on wavelet number, image resolution, and image compression. Some wavelets can enhance learning performance at reduced image resolutions, consistent with other melanoma feature-extraction studies.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Engineering, Multidisciplinary
Wenjing Wang, Xiang Li
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2020)
Article
Engineering, Electrical & Electronic
Jie-Ning Wu, Xiang Li, Guanrong Chen
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2020)
Article
Engineering, Electrical & Electronic
Huiyan Li, Xiang Li
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2020)
Article
Engineering, Electrical & Electronic
Dapeng Huang, Huiyan Li, Xiang Li
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2020)
Article
Mathematics, Interdisciplinary Applications
Cong Li, Jing Li, Xiang Li
Summary: This study analyzed the evolution mechanisms of temporal human contact networks and proposed a memory-driven model to simulate the networks. It also investigated the impact of infection spreading processes on the networks. The results showed that individual activity state transitions facilitate the spreading process, while contact establishment by active individuals suppresses it.
Article
Physics, Multidisciplinary
Xu Hao, Xiang Li
Summary: This letter discusses the urgency of accurately inferring network structure from easily observed data by introducing the heterogeneity of nodes. It proposes a novel method to estimate the importance of nodes directly from spreading results, which effectively improves inference accuracy, especially when observed data is insufficient.
Article
Automation & Control Systems
Jie Wu, Xiang Li
Summary: This article investigates global stochastic synchronization of Kuramoto-oscillator networks with duplex topological structures, introducing two scenarios of noise diffusion. It rigorously derives local and global connectivity criteria for achieving global stochastic asymptotic phase agreement and frequency synchronization. The theoretical results are validated through numerical simulation, showing that phase agreement is robust to noise perturbation while frequency synchronization is sensitive.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Proceedings Paper
Engineering, Electrical & Electronic
Jie Chen, Xiang Li
Summary: This paper investigates the application of memory-based best response update rule and bounded rational behavioral update rule to the vertex cover problem, proving that the bounded rational behavioral rule can ensure convergence of the entire vertex state to a SNE. Simulation experiments confirm the effectiveness of the proposed update rule, with findings suggesting that increasing the selection intensity leads to better SNE outcomes.
2021 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS)
(2021)
Article
Engineering, Multidisciplinary
Cong Li, Yuan Zhang, Xiang Li
Summary: This study investigates the role of layer preference and information spreading rate in controlling epidemic dynamics in temporal multiplex networks, revealing a new approach to controlling epidemic spreading through regulating epidemic threshold and promoting spreading process by nodes with higher degree displaying higher layer preference.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Rui Lv, Dingheng Wang, Jiangbin Zheng, Zhao-Xu Yang
Summary: In this paper, the authors investigate tensor decomposition for neural network compression. They analyze the convergence and precision of tensor mapping theory, validate the rationality of tensor mapping and its superiority over traditional tensor approximation based on the Lottery Ticket Hypothesis. They propose an efficient method called 3D-KCPNet to compress 3D convolutional neural networks using the Kronecker canonical polyadic (KCP) tensor decomposition. Experimental results show that 3D-KCPNet achieves higher accuracy compared to the original baseline model and the corresponding tensor approximation model.
Article
Computer Science, Artificial Intelligence
Xiangkun He, Zhongxu Hu, Haohan Yang, Chen Lv
Summary: In this paper, a novel constrained multi-objective reinforcement learning algorithm is proposed for personalized end-to-end robotic control with continuous actions. The approach trains a single model using constraint design and a comprehensive index to achieve optimal policies based on user-specified preferences.
Article
Computer Science, Artificial Intelligence
Zhijian Zhuo, Bilian Chen, Shenbao Yu, Langcai Cao
Summary: In this paper, a novel method called Expansion with Contraction Method for Overlapping Community Detection (ECOCD) is proposed, which utilizes non-negative matrix factorization to obtain disjoint communities and applies expansion and contraction processes to adjust the degree of overlap. ECOCD is applicable to various networks with different properties and achieves high-quality overlapping community detection.
Article
Computer Science, Artificial Intelligence
Yizhe Zhu, Chunhui Zhang, Jialin Gao, Xin Sun, Zihan Rui, Xi Zhou
Summary: In this work, the authors propose a Contrastive Spatio-Temporal Distilling (CSTD) approach to improve the detection of high-compressed deepfake videos. The approach leverages spatial-frequency cues and temporal-contrastive alignment to fully exploit spatiotemporal inconsistency information.
Review
Computer Science, Artificial Intelligence
Laijin Meng, Xinghao Jiang, Tanfeng Sun
Summary: This paper provides a review of coverless steganographic algorithms, including the development process, known contributions, and general issues in image and video algorithms. It also discusses the security of coverless steganography from theoretical analysis to actual investigation for the first time.
Article
Computer Science, Artificial Intelligence
Yajie Bao, Tianwei Xing, Xun Chen
Summary: Visual question answering requires processing multi-modal information and effective reasoning. Neural-symbolic learning is a promising method, but current approaches lack uncertainty handling and can only provide a single answer. To address this, we propose a confidence based neural-symbolic approach that evaluates NN inferences and conducts reasoning based on confidence.
Article
Computer Science, Artificial Intelligence
Anh H. Vo, Bao T. Nguyen
Summary: Interior style classification is an interesting problem with potential applications in both commercial and academic domains. This project proposes a method named ISC-DeIT, which combines data-efficient image transformer architectures and knowledge distillation, to address the interior style classification problem. Experimental results demonstrate a significant improvement in predictive accuracy compared to other state-of-the-art methods.
Article
Computer Science, Artificial Intelligence
Shashank Kotyan, Danilo Vasconcellos Vargas
Summary: This article introduces a novel augmentation technique called Dynamic Scanning Augmentation to improve the accuracy and robustness of Vision Transformer (ViT). The technique leverages dynamic input sequences to adaptively focus on different patches, resulting in significant changes in ViT's attention mechanism. Experimental results demonstrate that Dynamic Scanning Augmentation outperforms ViT in terms of both robustness to adversarial attacks and accuracy against natural images.
Article
Computer Science, Artificial Intelligence
Hiba Alqasir, Damien Muselet, Christophe Ducottet
Summary: The article proposes a solution to improve the learning process of a classification network by providing shape priors, reducing the need for annotated data. The solution is tested on cross-domain digit classification tasks and a video surveillance application.
Article
Computer Science, Artificial Intelligence
Dexiu Ma, Mei Liu, Mingsheng Shang
Summary: This paper proposes a method using neural dynamics solvers to solve infinity-norm optimization problems. Two improved solvers are constructed and their effectiveness and superiority are demonstrated through theoretical analysis and simulation experiments.
Article
Computer Science, Artificial Intelligence
Francesco Gregoretti, Giovanni Pezzulo, Domenico Maisto
Summary: Active Inference is a computational framework that uses probabilistic inference and variational free energy minimization to describe perception, planning, and action. cpp-AIF is a header-only C++ library that provides a powerful tool for implementing Active Inference for Partially Observable Markov Decision Processes through multi-core computing. It is cross-platform and improves performance, memory management, and usability compared to existing software.
Article
Computer Science, Artificial Intelligence
Zelin Ying, Dawei Cheng, Cen Chen, Xiang Li, Peng Zhu, Yifeng Luo, Yuqi Liang
Summary: This paper proposes a novel stock market trends prediction framework called SMART, which includes a self-supervised stock technical data sequence embedding model S3E. By training with multiple self-supervised auxiliary tasks, the model encodes stock technical data sequences into embeddings and uses the learned sequence embeddings for predicting stock market trends. Extensive experiments on China A-Shares market and NASDAQ market prove the high effectiveness of our model in stock market trends prediction, and its effectiveness is further validated in real-world applications in a leading financial service provider in China.
Article
Computer Science, Artificial Intelligence
Hao Li, Hao Jiang, Dongsheng Ye, Qiang Wang, Liang Du, Yuanyuan Zeng, Liu Yuan, Yingxue Wang, C. Chen
Summary: DHGAT1, a dynamic hyperbolic graph attention network, utilizes hyperbolic metric properties to embed dynamic graphs. It employs a spatiotemporal self-attention mechanism and weighted node representations, resulting in excellent performance in link prediction tasks.
Article
Computer Science, Artificial Intelligence
Jiehui Huang, Zhenchao Tang, Xuedong He, Jun Zhou, Defeng Zhou, Calvin Yu-Chian Chen
Summary: This study proposes a progressive learning multi-scale feature blending model for image deraining tasks. The model utilizes detail dilation and texture extraction to improve the restoration of rainy images. Experimental results show that the model achieves near state-of-the-art performance in rain removal tasks and exhibits better rain removal realism.
Article
Computer Science, Artificial Intelligence
Lizhi Liu, Zilin Gao, Yinhe Wang, Yongfu Li
Summary: This paper proposes a novel discrete-time interconnected model for depicting complex dynamical networks. The model consists of nodes and edges subsystems, which consider the dynamic characteristic of both nodes and edges. By designing control strategies and coupling modes, the stabilization and synchronization of the network are achieved. Simulation results demonstrate the effectiveness of the proposed methods.