Excitable scale free networks

Excitable Scale Free Networks

When a simple excitable system is continuously stimulated by a Poissonian external source, the response function (mean activity versus stimulus rate) generally shows a linear saturating shape. This is experimentally verified in some classes of sensory neurons, which accordingly present a small dynamic range (defined as the interval of stimulus intensity which can be appropriately coded by the m...

Excitable Greenberg-Hastings cellular automaton model on scale-free networks.

We study the excitable Greenberg-Hastings cellular automaton model on scale-free networks. We obtain analytical expressions for no external stimulus the uncoupled case. It is found that the curves, the average activity F versus the external stimulus rate r, can be fitted by a Hill function, but not exactly, there exists a relation F approximately r{alpha} for the low-stimulus response, where th...

Exactly scale-free scale-free networks

Many complex natural and physical systems exhibit patterns of interconnection that conform, approximately, to a network structure referred to as scale-free. Preferential attachment is one of many algorithms that have been introduced to model the growth and structure of scale-free networks. With so many different models of scale-free networks it is unclear what properties of scale-free networks ...

Deterministic Scale-Free Networks

Scale-free networks are abundant in nature, describing such diverse systems as the world wide web, the web of human sexual contacts, or the chemical network of a cell. All models used to generate a scale-free topology are stochastic, that is they create networks in which the nodes appear to be randomly connected to each other. Here we propose a simple model that generates scale-free networks in...

Scale-free networks