The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered ...The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.展开更多
In this paper, we apply a simple walk mechanism to the study of the traffic of many indistinguishable particles in complex networks. The network with particles stands for a particle system, and every vertex in the net...In this paper, we apply a simple walk mechanism to the study of the traffic of many indistinguishable particles in complex networks. The network with particles stands for a particle system, and every vertex in the network stands for a quantum state with the corresponding energy determined by the vertex degree. Although the particles are indistinguishable, the quantum states can be distinguished. When the many indistinguishable particles walk randomly in the system for a long enough time and the system reaches dynamic equilibrium, we find that under different restrictive conditions the particle distributions satisfy different forms, including the Bose Einstein distribution, the Fermi Dirac distribution and the non-Fermi distribution (as we temporarily call it). As for the Bose-Einstein distribution, we find that only if the particle density is larger than zero, with increasing particle density, do more and more particles condense in the lowest energy level. While the particle density is very low, the particle distribution transforms from the quantum statistical form to the classically statistical form, i.e., transforms from the Bose distribution or the Fermi distribution to the Boltzmann distribution. The numerical results fit well with the analytical predictions.展开更多
This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infectedrecovered diffusion process in a network with snapshot of partial nodes.We formulate the source id...This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infectedrecovered diffusion process in a network with snapshot of partial nodes.We formulate the source identification problem as a maximum likelihood(ML)estimator and develop a statistical inference method based on Monte Carlo simulation(MCS)to estimate the source location and the initial time of diffusion.Experimental results in synthetic networks and real-world networks demonstrate evident impact of the observation time as well as the fraction of the observers on the concerned problem.展开更多
In this paper, a dynamic epidemic control model on the uncorrelated complex networks is proposed. By means of theoretical analysis, we found that the new model has a similar epidemic threshold as that of the susceptib...In this paper, a dynamic epidemic control model on the uncorrelated complex networks is proposed. By means of theoretical analysis, we found that the new model has a similar epidemic threshold as that of the susceptible-infectedrecovered (SIR) model on the above networks, but it can reduce the prevalence of the infected individuals remarkably. This result may help us understand epidemic spreading phenomena on real networks and design appropriate strategies to control infections.展开更多
Domination is the fastest-growing field within graph theory with a profound diversity and impact in real-world applications,such as the recent breakthrough approach that identifies optimized subsets of proteins enrich...Domination is the fastest-growing field within graph theory with a profound diversity and impact in real-world applications,such as the recent breakthrough approach that identifies optimized subsets of proteins enriched with cancer-related genes.Despite its conceptual simplicity,domination is a classical NP-complete decision problem which makes analytical solutions elusive and poses difficulties to design optimization algorithms for finding a dominating set of minimum cardinality in a large network.Here,we derive for the first time an approximate analytical solution for the density of the minimum dominating set(MDS)by using a combination of cavity method and ultra-discretization(UD)procedure.The derived equation allows us to compute the size of MDS by only using as an input the information of the degree distribution of a given network.展开更多
We introduce Tsallis mapping in Bianconi-Barabgsi (B-B) fitness model of growing networks. This mapping addresses the dynamical behavior of the fitness model within the framework of nonextensive statistics mechanics...We introduce Tsallis mapping in Bianconi-Barabgsi (B-B) fitness model of growing networks. This mapping addresses the dynamical behavior of the fitness model within the framework of nonextensive statistics mechanics, which is characterized by a dimensionless nonextensivity parameter q. It is found that this new phenomenological parameter plays an important role in the evolution of networks: the underlying evolving networks may undergo a different phases depending on the q exponents, comparing to the original B-B fitness model, and the corresponding critical transition temperature Tc is also identified.展开更多
Many real-world networks have the ability to adapt themselves in response to the state of their nodes. This paper studies controlling disease spread on network with feedback mechanism, where the susceptible nodes are ...Many real-world networks have the ability to adapt themselves in response to the state of their nodes. This paper studies controlling disease spread on network with feedback mechanism, where the susceptible nodes are able to avoid contact with the infected ones by cutting their connections with probability when the density of infected nodes reaches a certain value in the network. Such feedback mechanism considers the networks' own adaptivity and the cost of immunization. The dynamical equations about immunization with feedback mechanism ave solved and theoretical predictions are in agreement with the results of large scale simulations. It shows that when the lethality a increases, the prevalence decreases more greatly with the same immunization g. That is, with the same cost, a better controlling result can be obtained. This approach offers an effective and practical policy to control disease spread, and also may be relevant to other similar networks.展开更多
Self-organization theory informs an analysis on the evolution of labor self-organizations (LSOs), but lacks technical analysis on the evolution of their organizational structures. Fortunately, complex network technolo...Self-organization theory informs an analysis on the evolution of labor self-organizations (LSOs), but lacks technical analysis on the evolution of their organizational structures. Fortunately, complex network technology offers a new approach to analyzing these structures. Built on an extension of the Barabási-Albert (BA) model, we can simulate the evolution of LSOs by analyzing indicators including the clustering coefficient, degree distribution (DD) and average path length (APL) of workers, thereby demonstrating the evolving patterns of LSOs. Accordingly, governmental mechanism designs based on such patterns may not only stimulate energy growth and functional realization of LSOs, but also reduce the social percussions of abrupt evolutions. A comparative analysis of the evolutionary trajectories of LSOs in China and the U.S. finds that the U.S. government’s mechanism designs for protecting capitalism not only prevented the effective gathering of workers, but also prolonged the history of industrial conflicts. Such mechanism designs also led to the early dispersion and decline of LSOs and hindered the evolution of the working class. In contrast, the Chinese government established a socialist system that allowed workers to become the underlying force of socialist productivity. This design reduced labor strife while accelerating the evolution of workers towards higher stages.展开更多
A statistical mechanics framework of fuzzy random polymer networks is established based on the theories of fuzzy systems. The entanglement effect is manifested quantitatively by introducing an entanglement tensor and ...A statistical mechanics framework of fuzzy random polymer networks is established based on the theories of fuzzy systems. The entanglement effect is manifested quantitatively by introducing an entanglement tensor and membership function and the amorphous structure is treated as the fuzzy random network made up of macromolecular coils entangled randomly. A random tetrahedral entangled-crosslinked cell is chosen as an average representative unit of the fuzzy random polymer network structure. By making use of the theory of fuzzy probability and statistical mechanics, the expression for the free energy of deformation is given, which fits well with the experimental data on rubber elasticity under various deformation modes. Both classical statistical theory and Mooney-Rivlin equation can be taken as its special cases.展开更多
基金supported in part by the National Natural Science Foundation of China (62233012,62273087)the Research Fund for the Taishan Scholar Project of Shandong Province of Chinathe Shanghai Pujiang Program of China (22PJ1400400)。
文摘The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.
基金supported by the National Natural Science Foundation of China (Grant No 10875012)the High Performance Science Computing Center of Beijing Normal University of China
文摘In this paper, we apply a simple walk mechanism to the study of the traffic of many indistinguishable particles in complex networks. The network with particles stands for a particle system, and every vertex in the network stands for a quantum state with the corresponding energy determined by the vertex degree. Although the particles are indistinguishable, the quantum states can be distinguished. When the many indistinguishable particles walk randomly in the system for a long enough time and the system reaches dynamic equilibrium, we find that under different restrictive conditions the particle distributions satisfy different forms, including the Bose Einstein distribution, the Fermi Dirac distribution and the non-Fermi distribution (as we temporarily call it). As for the Bose-Einstein distribution, we find that only if the particle density is larger than zero, with increasing particle density, do more and more particles condense in the lowest energy level. While the particle density is very low, the particle distribution transforms from the quantum statistical form to the classically statistical form, i.e., transforms from the Bose distribution or the Fermi distribution to the Boltzmann distribution. The numerical results fit well with the analytical predictions.
基金the National Natural Science Foundation of China(Grant Nos.61673027 and 62106047)the Beijing Social Science Foundation(Grant No.21GLC042)the Humanity and Social Science Youth foundation of Ministry of Education,China(Grant No.20YJCZH228)。
文摘This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infectedrecovered diffusion process in a network with snapshot of partial nodes.We formulate the source identification problem as a maximum likelihood(ML)estimator and develop a statistical inference method based on Monte Carlo simulation(MCS)to estimate the source location and the initial time of diffusion.Experimental results in synthetic networks and real-world networks demonstrate evident impact of the observation time as well as the fraction of the observers on the concerned problem.
基金Project supported by the National Natural Science Foundation of China (Grant No.60774088)the Program for New Century Excellent Talents of Higher Education of China (Grant No NCET 2005-290)the Special Research Fund for the Doctoral Program of Higher Education of China (Grant No 20050055013)
文摘In this paper, a dynamic epidemic control model on the uncorrelated complex networks is proposed. By means of theoretical analysis, we found that the new model has a similar epidemic threshold as that of the susceptible-infectedrecovered (SIR) model on the above networks, but it can reduce the prevalence of the infected individuals remarkably. This result may help us understand epidemic spreading phenomena on real networks and design appropriate strategies to control infections.
基金partially supported by MEXT,Japan(Grant-in-Aid No.25330351)T.O.was partially supported by JSPS Grant-in-Aid for Scientific Research(Grant Number 15K01200)Otsuma Grant-in Aid for Individual Exploratory Research(Grant Number S2609).
文摘Domination is the fastest-growing field within graph theory with a profound diversity and impact in real-world applications,such as the recent breakthrough approach that identifies optimized subsets of proteins enriched with cancer-related genes.Despite its conceptual simplicity,domination is a classical NP-complete decision problem which makes analytical solutions elusive and poses difficulties to design optimization algorithms for finding a dominating set of minimum cardinality in a large network.Here,we derive for the first time an approximate analytical solution for the density of the minimum dominating set(MDS)by using a combination of cavity method and ultra-discretization(UD)procedure.The derived equation allows us to compute the size of MDS by only using as an input the information of the degree distribution of a given network.
基金Supported by the National Natural Science Foundation of China under Grant No. 10875058the Initiative Plan of Shanghai Education Committee under Grant No. 10YZ76the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry (SRF for ROCS,SEM)
文摘We introduce Tsallis mapping in Bianconi-Barabgsi (B-B) fitness model of growing networks. This mapping addresses the dynamical behavior of the fitness model within the framework of nonextensive statistics mechanics, which is characterized by a dimensionless nonextensivity parameter q. It is found that this new phenomenological parameter plays an important role in the evolution of networks: the underlying evolving networks may undergo a different phases depending on the q exponents, comparing to the original B-B fitness model, and the corresponding critical transition temperature Tc is also identified.
基金Project supported by the National Natural Science Foundation of China (Grant No 10375022).
文摘Many real-world networks have the ability to adapt themselves in response to the state of their nodes. This paper studies controlling disease spread on network with feedback mechanism, where the susceptible nodes are able to avoid contact with the infected ones by cutting their connections with probability when the density of infected nodes reaches a certain value in the network. Such feedback mechanism considers the networks' own adaptivity and the cost of immunization. The dynamical equations about immunization with feedback mechanism ave solved and theoretical predictions are in agreement with the results of large scale simulations. It shows that when the lethality a increases, the prevalence decreases more greatly with the same immunization g. That is, with the same cost, a better controlling result can be obtained. This approach offers an effective and practical policy to control disease spread, and also may be relevant to other similar networks.
基金a deliverable of the “Research on the Accounting of ‘Trade in Value-added’ in Chinese Services Sector and its Place in the Global Value Chain,” a project funded by the National Social Science Foundation of China(15BGJ036)“The Impacts of Economic Globalization on Entrepreneurship in China—Theoretical Research and Empirical Analysis,” a youth project funded by the National Natural Science Foundation of China(NSFC)(71603142)+3 种基金“Research on Approaches to Labor-Management Cooperation with Chinese Characteristics—A Labor Relations Evolutionary Perspective,” a Ministry of Education humanities and social sciences research youth project(16YJC790115)“Research on the Evolution of Labor Relations with Chinese Characteristics Since the 18th CPC National Congress,” a Shandong planned social sciences research project(16CZLJ05)“Research on the Evolution Mechanisms and Paths of the Marxist Labor System from a Complex Network Perspective,” a project funded by the China Postdoctoral Science Foundation(CPSF)(2017M612180)“Research on Mechanism Design of the Spatial Structure of Labor-Management Cooperation with Chinese Characteristics,” a Qingdao postdoctoral applied research project
文摘Self-organization theory informs an analysis on the evolution of labor self-organizations (LSOs), but lacks technical analysis on the evolution of their organizational structures. Fortunately, complex network technology offers a new approach to analyzing these structures. Built on an extension of the Barabási-Albert (BA) model, we can simulate the evolution of LSOs by analyzing indicators including the clustering coefficient, degree distribution (DD) and average path length (APL) of workers, thereby demonstrating the evolving patterns of LSOs. Accordingly, governmental mechanism designs based on such patterns may not only stimulate energy growth and functional realization of LSOs, but also reduce the social percussions of abrupt evolutions. A comparative analysis of the evolutionary trajectories of LSOs in China and the U.S. finds that the U.S. government’s mechanism designs for protecting capitalism not only prevented the effective gathering of workers, but also prolonged the history of industrial conflicts. Such mechanism designs also led to the early dispersion and decline of LSOs and hindered the evolution of the working class. In contrast, the Chinese government established a socialist system that allowed workers to become the underlying force of socialist productivity. This design reduced labor strife while accelerating the evolution of workers towards higher stages.
文摘A statistical mechanics framework of fuzzy random polymer networks is established based on the theories of fuzzy systems. The entanglement effect is manifested quantitatively by introducing an entanglement tensor and membership function and the amorphous structure is treated as the fuzzy random network made up of macromolecular coils entangled randomly. A random tetrahedral entangled-crosslinked cell is chosen as an average representative unit of the fuzzy random polymer network structure. By making use of the theory of fuzzy probability and statistical mechanics, the expression for the free energy of deformation is given, which fits well with the experimental data on rubber elasticity under various deformation modes. Both classical statistical theory and Mooney-Rivlin equation can be taken as its special cases.