TY - JOUR A1 - Li, Ping A1 - Chen, Maoyin A1 - Wu, Ye A1 - Kurths, Jürgen T1 - Matrix-measure criterion for synchronization in coupled-map networks N2 - We present conditions for the local and global synchronizations in coupled-map networks using the matrix measure approach. In contrast to many existing synchronization conditions, the proposed synchronization criteria do not depend on the solution of the synchronous state and give less limitation on the network connections. Numerical simulations of the coupled quadratic maps demonstrate the potentials of our main results. Y1 - 2009 UR - http://pre.aps.org/ U6 - https://doi.org/10.1103/Physreve.79.067102 SN - 1539-3755 ER - TY - JOUR A1 - Wu, Ye A1 - Li, Ping A1 - Chen, Maoyin A1 - Xiao, Jinghua A1 - Kurths, Jürgen T1 - Response of scale-free networks with community structure to external stimuli N2 - The response of scale-free networks with community structure to external stimuli is studied. By disturbing some nodes with different strategies, it is shown that the robustness of this kind of network can be enhanced due to the existence of communities in the networks. Some of the response patterns are found to coincide with topological communities. We show that such phenomena also occur in the cat brain network which is an example of a scale-free like network with community structure. Our results provide insights into the relationship between network topology and the functional organization in complex networks from another viewpoint. Y1 - 2009 UR - http://www.sciencedirect.com/science/journal/03784371 U6 - https://doi.org/10.1016/j.physa.2009.03.037 SN - 0378-4371 ER - TY - JOUR A1 - Chen, Maoyin A1 - Shang, Yun A1 - Zhou, Changsong A1 - Wu, Ye A1 - Kurths, Jürgen T1 - Enhanced synchronizability in scale-free networks N2 - We introduce a modified dynamical optimization coupling scheme to enhance the synchronizability in the scale- free networks as well as to keep uniform and converging intensities during the transition to synchronization. Further, the size of networks that can be synchronizable exceeds by several orders of magnitude the size of unweighted networks. Y1 - 2009 UR - http://chaos.aip.org/ U6 - https://doi.org/10.1063/1.3062864 SN - 1054-1500 ER - TY - JOUR A1 - Wu, Ye A1 - Zhou, Changsong A1 - Chen, Maoyin A1 - Xiao, Jinghua A1 - Kurths, Jürgen T1 - Human comment dynamics in on-line social systems N2 - Human comment is studied using data from 'tianya' which is one of the most popular on-line social systems in China. We found that the time interval between two consecutive comments on the same topic, called inter-event time, follows a power-law distribution. This result shows that there is no characteristic decay time on a topic. It allows for very long periods without comments that separate bursts of intensive comments. Furthermore, the frequency of a different ID commenting on a topic also follows a power-law distribution. It indicates that there are some "hubs" in the topic who lead the direction of the public opinion. Based on the personal comments habit, a model is introduced to explain these phenomena. The numerical simulations of the model fit well with the empirical results. Our findings are helpful for discovering regular patterns of human behavior in on-line society and the evolution of the public opinion on the virtual as well as real society. Y1 - 2010 UR - http://www.sciencedirect.com/science/journal/03784371 U6 - https://doi.org/10.1016/j.physa.2010.08.049 SN - 0378-4371 ER - TY - THES A1 - Wu, Ye T1 - Nonlinear dynamics in complex networks and modeling human dynamics T1 - Nichtlineare Dynamik in komplexen Netzwerken und Modellierung menschlicher Dynamik N2 - Durch große Datenmengen können die Forscher die Eigenschaften komplexer Systeme untersuchen, z.B. komplexe Netzwerk und die Dynamik des menschlichen Verhaltens. Eine große Anzahl an Systemen werden als große und komplexe Netzwerke dargestellt, z.B. das Internet, Stromnetze, Wirtschaftssysteme. Immer mehr Forscher haben großes Interesse an der Dynamik des komplexen Netzwerks. Diese Arbeit besteht aus den folgenden drei Teilen. Der erste Teil ist ein einfacher dynamischer Optimierungs-Kopplungs-Mechanismus, aber sehr wirksam. Durch den Mechanismus kann synchronisation in komplexen Netzwerken mit und ohne Zeitverzögerung realisiert, und die Fähigkeit der Synchronisation von small-world und scale-free Netze verbessert werden. Im zweiten Teil geht um die Verstärkung der Robustheit der scale-free Netze im Zusammenhang mit der Gemeinden-Struktur. Einige Reaktionsmuster und topologische Gemeinden sind einheitlich. Die Ergebnisse zeigen einen neuen Aspekt der Beziehung zwischen den Funktionen und der Netzwerk-Topologie von komplexen Netzwerken. Im dritten Teil welche eine wichtige Rolle in komplexen Netzwerken spielt, wird die Verhaltens-Dynamik der menschliche Mitteilung durch Daten- und Modellanalysierung erforscht, dann entsteht ein neues Mitteilungsmodell. Mit Hilfe von einem Interaktion priority-Queue Model kann das neue Modell erklärt werden. Mit Hilfe des Models können viele praktische Interaktions-Systeme erklärt werden, z.B. E-Mail und Briefe (oder Post). Mit Hilfe meiner Untersuchung kann man menschliches Verhalten auf der Individuums- und Netzwerkebene neu kennenlernen. Im vierter Teil kann ich nachweisen, dass menschliches Kommentar-Verhalten in on-line Sozialsystemen, eine andere Art der Interaktionsdynamik von Mensch non-Poisson ist und dieses am Modell erklären. Mit Hilfe der non-Poisson Prozesse kann man das persönliche Anziehungskraft-Modell besser verstehen. Die Ergebnisse sind hilfreich zum Kennenlernen des Musters des menschlichen Verhaltens in on-line Gesellschaften und der Entwicklung von öffentlicher Meinung nicht nur in der virtuellen Gesellschaftn sondern auch in der Realgesellschaft. Am Ende geht es um eine Prognose von menschlicher Dynamik und komplexen Netzwerken. N2 - The availability of large data sets has allowed researchers to uncover complex properties in complex systems, such as complex networks and human dynamics. A vast number of systems, from the Internet to the brain, power grids, ecosystems, can be represented as large complex networks. Dynamics on and of complex networks has attracted more and more researchers’ interest. In this thesis, first, I introduced a simple but effective dynamical optimization coupling scheme which can realize complete synchronization in networks with undelayed and delayed couplings and enhance the small-world and scale-free networks’ synchronizability. Second, I showed that the robustness of scale-free networks with community structure was enhanced due to the existence of communities in the networks and some of the response patterns were found to coincide with topological communities. My results provide insights into the relationship between network topology and the functional organization in complex networks from another viewpoint. Third, as an important kind of nodes of complex networks, human detailed correspondence dynamics was studied by both data and the model. A new and general type of human correspondence pattern was found and an interacting priority-queues model was introduced to explain it. The model can also embrace a range of realistic social interacting systems such as email and letter communication. My findings provide insight into various human activities both at the individual and network level. Fourth, I present clearly new evidence that human comment behavior in on-line social systems, a different type of interacting human dynamics, is non-Poissonian and a model based on the personal attraction was introduced to explain it. These results are helpful for discovering regular patterns of human behavior in on-line society and the evolution of the public opinion on the virtual as well as real society. Finally, there are conclusion and outlook of human dynamics and complex networks. KW - komplexe Netzwerke KW - menschliche Dynamik KW - complex networks KW - human dynamics Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-47358 ER -