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Ying-Hai Wang

Publications and source records attributed to Ying-Hai Wang.

5 recordsLinked to original sources
PubMed2006

Effects of degree distribution in mutual synchronization of neural networks.

We study the effects of the degree distribution in mutual synchronization of two-layer neural networks. We carry out three coupling strategies: large-large coupling, random coupling, and small-small coupling. By computer simulations and analytical methods, we find that couplings between nodes with large degree play an important role in the synchronization. For large-large coupling, less couplings are needed for inducing synchronization for both random and scale-free networks. For random coupling, cutting couplings between nodes with large degree is very efficient for preventing neural systems from synchronization, especially when subnetworks are scale free.

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PubMed2006

Evolutionary prisoner's dilemma game with dynamic preferential selection.

We study a modified prisoner's dilemma game taking place on two-dimensional disordered square lattices. The players are pure strategists and can either cooperate or defect with their immediate neighbors. In the generations each player updates its strategy by following one of the neighboring strategies with a probability dependent on the payoff difference. The neighbor selection obeys a dynamic preferential rule, i.e., the more frequently a neighbor's strategy was adopted by the focal player in the previous rounds, the larger probability it will be chosen to refer to in the subsequent rounds. It is found that cooperation is substantially promoted due to this simple selection mechanism. Corresponding analysis is provided by the investigation of the distribution of the players' impact weights, persistence, and correlation function.

Journal Article↗
PubMed2005

Generating structured networks based on a weight-dependent deactivation mechanism.

Motivated by the degree-dependent deactivation model generating networks with high clustering coefficient [K. Klemm, Phys. Rev. E. 65, 036123 (2002)], a weight-dependent version is studied to model evolving networks. The growth dynamics of the network is based on a naive weight-driven deactivation mechanism which couples the establishment of new active vertices and the weights' dynamical evolution. Both analytical solutions and numerical simulations show that the generated networks possess a high clustering coefficient larger than that for regular lattices of the same average connectivity. Weighted, structured scale-free networks are obtained as the deactivated vertex is target selected at each time step, and weighted, structured exponential networks are realized for the random-selected case.

Journal Article↗
PubMed2005

Spatial prisoner's dilemma game with volunteering in Newman-Watts small-world networks.

A modified spatial prisoner's dilemma game with voluntary participation in Newman-Watts small-world networks is studied. Some reasonable ingredients are introduced to the game evolutionary dynamics: each agent in the network is a pure strategist and can only take one of three strategies (cooperator, defector, and loner); its strategical transformation is associated with both the number of strategical states and the magnitude of average profits, which are adopted and acquired by its coplayers in the previous round of play; a stochastic strategy mutation is applied when it gets into the trouble of local commons that the agent and its neighbors are in the same state and get the same average payoffs. In the case of very low temptation to defect, it is found that agents are willing to participate in the game in typical small-world region and intensive collective oscillations arise in more random region.

Journal Article↗