In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on… (More)
As this review describes, coupled time series can be analyzed by different methods, including complex network and random matrix approaches.
Power law degree distribution was shown in many complex networks. However, in most real systems, deviation from power-law behavior is observed in social and economical networks and emergence of giant hubs is obvious in real network structures far from the tail of power law. We propose a model based on the information transparency (transparency means how… (More)
In the context of network dynamics, the complexity of systems increases possible evolutionary paths that often are not deterministic. Occasionally, some map routs form over the course of time which guide systems towards some particular states. The main intention of this study is to discover an indicator that can help predict these pseudo-deterministic paths… (More)
BACKGROUND Classification of medical sciences into its sub-branches is crucial for optimum administration of healthcare and specialty training. Due to the rapid and continuous evolution of medical sciences, development of unbiased tools for monitoring the evolution of medical disciplines is required. METHODOLOGY/PRINCIPAL FINDINGS Network analysis was… (More)
Growth dynamic of real networks because of emerging complexities is an open and interesting question. Indeed it is not realistic to ignore history impact on the current events. The mystery behind that complexity could be in the role of history in some how. To regard this point, the average effect of history has been included by a kernel function in… (More)
S tudying the behavior of a single system (subsystem) without considering its interactions with the other systems (subsystems) doesn't give holistic information about this system. So, we should consider coupled systems as a community in which these systems interact and self-organize their internal structures with each other. Many researchers have attempted… (More)