Gaogao Dong

A new hyperchaotic system and its synchronization

In this paper, a four-dimensional (4D) continuous autonomous hyperchaotic system is introduced and analyzed. This hyperchaotic system is constructed by adding a linear controller to the 3D autonomous chaotic system with a reverse butterfly-shape attractor. Some of its basic dynamical properties, such as Lyapunov exponents, Poincare section, bifurcation diagram and the periodic orbits evolving into chaotic, hyperchaotic dynamical behavior by varying parameter d are studied. Furthermore, the full state hybrid projective synchronization (FSHPS) of new hyperchaotic system with unknown parameters including the unknown coefficients of nonlinear terms is studied by using adaptive control. Numerical simulations are presented to show the effective of the proposed chaos synchronization scheme.

Modified localized attack on complex network

Since a shell structure contains a wealth of information, it is not only very important for understanding the transport properties of the network, but also essential to identify influential spreaders in complex networks. Nodes within each shell can be classified into two categories: protected nodes and unprotected nodes. In this paper, we propose a generalization of the localized attack, modified localized attack, which means that when a randomly chosen node (root node) is under attack, protected nodes will not be removed, but unprotected nodes in the nearest shells will fail. We numerically and analytically study the system robustness under this attack by taking an Erdos-Renyi (ER) network, a regular random (RR) network and a scale-free (SF) network as examples. Moreover, a fraction of nodes belonging to giant component S and a critical threshold q c , where S approaches to zero, are given. The result implies that increasing connection density has been found to be useful to significantly improve network robustness.

Percolation on interacting networks with feedback-dependency links

When real networks are considered, coupled networks with connectivity and feedback-dependency links are not rare but more general. Here, we develop a mathematical framework and study numerically and analytically the percolation of interacting networks with feedback-dependency links. For the case that all degree distributions of intra- and inter- connectivity links are Poissonian, we find that for a low density of inter-connectivity links, the system undergoes from second order to first order through hybrid phase transition as coupling strength increases. It implies that the average degree k of inter-connectivity links has a little influence on robustness of the system with a weak coupling strength, which corresponds to the second order transition, but for a strong coupling strength corresponds to the first order transition. That is to say, the system becomes robust as k increases. However, as the average degree k of each network increases, the system becomes robust for any coupling strength. In addition, we find that one can take less cost to design robust system as coupling strength decreases by analyzing minimum average degree kmin of maintaining system stability. Moreover, for high density of inter-connectivity links, we find that the hybrid phase transition region disappears, the first order region becomes larger and second order region becomes smaller. For the case of two coupled scale-free networks, the system also undergoes from second order to first order through hybrid transition as the coupling strength increases. We find that for a weak coupling strength, which corresponds to the second order transitions, feedback dependency links have no effect on robustness of system relative to no-feedback condition, but for strong coupling strength which corresponds to first order or hybrid phase transition, the system is more vulnerable under feedback condition comparing with no-feedback condition. Thus, for designing resilient system, designers should try to avoid the feedback dependency links, because the existence of feedback-dependency links makes the system extremely vulnerable and difficult to defend.

Spatiotemporal Dynamics and Fitness Analysis of Global Oil Market: Based on Complex Network

We study the overall topological structure properties of global oil trade network, such as degree, strength, cumulative distribution, information entropy and weight clustering. The structural evolution of the network is investigated as well. We find the global oil import and export networks do not show typical scale-free distribution, but display disassortative property. Furthermore, based on the monthly data of oil import values during 2005.01–2014.12, by applying random matrix theory, we investigate the complex spatiotemporal dynamic from the country level and fitness evolution of the global oil market from a demand-side analysis. Abundant information about global oil market can be obtained from deviating eigenvalues. The result shows that the oil market has experienced five different periods, which is consistent with the evolution of country clusters. Moreover, we find the changing trend of fitness function agrees with that of gross domestic product (GDP), and suggest that the fitness evolution of oil market can be predicted by forecasting GDP values. To conclude, some suggestions are provided according to the results.

SUDDEN OCCURRENCE OF CHAOS-II IN NONSMOOTH MAPS

This paper introduces a type of one-dimensional nonsmooth nonlinear discrete dynamic system. We find a direct route to chaos from stable period-two point, and this is called Sudden Occurrence of Chaos. It is completely different from the three routes from regular motion to chaos — period-doubling bifurcation chaos, intermittency and quasi-periodicity chaos. Furthermore, we present some examples of sudden occurrence of chaos from m-period directly to chaos.