In the present paper, synchronization and bifurcation of general complex dynamical networks are investigated. We mainly focus on networks with a somewhat general coupling matrix, i.e., the sum of each row equals a non...In the present paper, synchronization and bifurcation of general complex dynamical networks are investigated. We mainly focus on networks with a somewhat general coupling matrix, i.e., the sum of each row equals a nonzero constant u. We derive a result that the networks can reach a new synchronous state, which is not the asymptotic limit set determined by the node equation. At the synchronous state, the networks appear bifurcation if we regard the constant u as a bifurcation parameter. Numerical examples are given to illustrate our derived conclusions.展开更多
Synchronization and bifurcation analysis in coupled networks of discrete-time systems are investigated in the present paper. We mainly focus on some special coupling matrix, i.e., the sum of each row equals a nonzero ...Synchronization and bifurcation analysis in coupled networks of discrete-time systems are investigated in the present paper. We mainly focus on some special coupling matrix, i.e., the sum of each row equals a nonzero constant u and the network connection is directed. A result that the network can reach a new synchronous state, which is not the asymptotic limit set determined by the node state equation, is derived. It is interesting that the network exhibits bifurcation if we regard the constant u as a bifurcation parameter at the synchronous state. Numerical simulations are given to show the efficiency of our derived conclusions.展开更多
In clinical practice,brain death is the irreversible end of all brain activity.Compared to current statistical methods for the determination of brain death,we focus on the approach of complex networks for real-world e...In clinical practice,brain death is the irreversible end of all brain activity.Compared to current statistical methods for the determination of brain death,we focus on the approach of complex networks for real-world electroencephalography in its determination.Brain functional networks constructed by correlation analysis are derived,and statistical network quantities used for distinguishing the patients in coma or brain death state,such as average strength,clustering coefficient and average path length,are calculated.Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state.Our findings might provide valuable insights on the determination of brain death.展开更多
基金The project supported by National Natural Science Foundation of China under Grant No, 70431002
文摘In the present paper, synchronization and bifurcation of general complex dynamical networks are investigated. We mainly focus on networks with a somewhat general coupling matrix, i.e., the sum of each row equals a nonzero constant u. We derive a result that the networks can reach a new synchronous state, which is not the asymptotic limit set determined by the node equation. At the synchronous state, the networks appear bifurcation if we regard the constant u as a bifurcation parameter. Numerical examples are given to illustrate our derived conclusions.
基金The project supported by the Key Programm Projects of the National Natural Science Foundation of China under Grant No. 70431002, the SRF for R0CS, SEM and the Graduate Student Innovation Foundation of Shanghai University
文摘Synchronization and bifurcation analysis in coupled networks of discrete-time systems are investigated in the present paper. We mainly focus on some special coupling matrix, i.e., the sum of each row equals a nonzero constant u and the network connection is directed. A result that the network can reach a new synchronous state, which is not the asymptotic limit set determined by the node state equation, is derived. It is interesting that the network exhibits bifurcation if we regard the constant u as a bifurcation parameter at the synchronous state. Numerical simulations are given to show the efficiency of our derived conclusions.
基金by the National Natural Science Foundation of China under Grant Nos 10672057 and 10872068the Fundamental Research Funds for the Central Universities and Japan Society for the Promotion of Science(22560425).
文摘In clinical practice,brain death is the irreversible end of all brain activity.Compared to current statistical methods for the determination of brain death,we focus on the approach of complex networks for real-world electroencephalography in its determination.Brain functional networks constructed by correlation analysis are derived,and statistical network quantities used for distinguishing the patients in coma or brain death state,such as average strength,clustering coefficient and average path length,are calculated.Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state.Our findings might provide valuable insights on the determination of brain death.
