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Proceedings Paper

Spatial-temporal structures in noise processes: microscopic and macroscopic dynamics
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Paper Abstract

Noise processes are often modelled as stochastic processes. We have used a multivariate method based on the application of Principal Component Analysis (PCA) in order to classify different spatial-temporal structures taken as noise. When the structures have a correlation in time, a parameter distinguishing between fast and slow dynamics appears naturally. We have found this parameter in previous contributions with a different meaning depending on the context. Especially interesting is the application to the characterization of 1/f noise. In this paper we have extended the method in order to apply it to different kind of systems exhibiting, for example, self-organizing properties or brownian motion. One goal is trying to define a criterion to distinguish between fast and slow dynamics parameters. Finally, a statistical analysis is made in order to find the conditions for the application of the method to a wide range of different systems.

Paper Details

Date Published: 25 May 2004
PDF: 11 pages
Proc. SPIE 5471, Noise in Complex Systems and Stochastic Dynamics II, (25 May 2004); doi: 10.1117/12.547079
Show Author Affiliations
Jose Manuel Lopez-Alonso, Univ. Complutense de Madrid (Spain)
Javier Alda, Univ. Complutense de Madrid (Spain)


Published in SPIE Proceedings Vol. 5471:
Noise in Complex Systems and Stochastic Dynamics II
Zoltan Gingl, Editor(s)

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