We analyzed the dependence structure of the credit and stock market using random matrix theory and network topology. The dynamics of both markets have been spotlighted throughout the subprime crisis. In this study, we compared these two markets in view of the market-wide effect from random...

Sparse-code networks have retrieval abilities which are strongly dependent on the firing threshold for the neurons. If the connections are spatially uniform, the macroscopic properties of the network can be measured by the overlap between neurons and learned patterns, and by the global activity....

This paper investigates the adaptation of cooperating strategies in an iterated prisoner's dilemma (IPD) game with individually learning agents, subject to the structure of the interaction network. In particular, we study how cooperation or defection comes to dominate the population on...

The urban road network is a complex system that exhibits the properties of self-organization and emergence. Recent theoretical and empirical studies have mainly focused on the structural properties of the urban road networks. This research concentrates on some important parameters such as...

We show that the use of a minimal spanning tree (MST) to filter important information in a complex system is not robust except when the system contains a unique MST. In this paper we propose to use the forest of all MSTs as a robust filter. According to this filter, centrality measures are also...

A network’s transmission capacity is the maximal rate of traffic inflow that the network can handle without causing congestion. Here we study how to enhance this quantity by allocating resource to individual nodes while preserving the total amount of the resource available. We propose a...