dc.contributor |
Centre de Recerca Matemàtica |
dc.contributor.author |
Corral, Álvaro |
dc.date.accessioned |
2009-04-27T07:34:35Z |
dc.date.available |
2009-04-27T07:34:35Z |
dc.date.created |
2008-10 |
dc.date.issued |
2008-10 |
dc.identifier.uri |
http://hdl.handle.net/2072/15543 |
dc.format.extent |
19 |
dc.format.extent |
148759 bytes |
dc.format.mimetype |
application/pdf |
dc.language.iso |
eng |
dc.publisher |
Centre de Recerca Matemàtica |
dc.relation.ispartofseries |
Prepublicacions del Centre de Recerca Matemàtica;834 |
dc.rights |
Aquest document està subjecte a una llicència d'ús de Creative Commons, amb la qual es permet copiar, distribuir i comunicar públicament l'obra sempre que se'n citin l'autor original, la universitat i el centre i no se'n faci cap ús comercial ni obra derivada, tal com queda estipulat en la llicència d'ús (http://creativecommons.org/licenses/by-nc-nd/2.5/es/) |
dc.title |
Point-occurrence self-similarity in crackling-noise systems and in other complex systems |
dc.type |
info:eu-repo/semantics/preprint |
dc.subject.udc |
68 - Indústries, oficis i comerç d'articles acabats. Tecnologia cibernètica i automàtica |
dc.description.abstract |
It has been recently found that a number of systems displaying crackling noise also show a remarkable behavior regarding the temporal occurrence of successive events versus their size: a scaling law for the probability distributions of waiting times as a function of a minimum size is fulfilled, signaling
the existence on those systems of self-similarity in time-size. This property is also present in some non-crackling systems. Here, the uncommon character of
the scaling law is illustrated with simple marked renewal processes, built by definition
with no correlations. Whereas processes with a finite mean waiting time do not fulfill a scaling law in general and tend towards a Poisson process in the limit of very high sizes, processes without a finite mean tend to another class of distributions, characterized by double power-law waiting-time densities. This is somehow reminiscent of the generalized central limit theorem. A model with short-range correlations is not able to escape from the attraction of those limit distributions. A discussion on open problems in the modeling of these properties is provided. |