The mass transfer in a film of metal-organic framework with one-dimensional pores, oriented perpendicular to the substrate surface, was explored. The diffusion coefficients of the probe molecules, cyclohexane and p-xylene were determined f...
Artikel
The Different Types of Noise and How They Effect Data Analysis
Von Wiley-VCH zur Verfügung gestellt
Many noisy data in our daily life are not independent but exhibit short or long range correlations. The different kinds of correlations can considerably inuence the structure of a record and thus need to be considered in data analysis, in particular in the analysis of climate records that are known to exhibit long-range correlations.
Abstract
Random (noisy) processes can be characterized by the way consecutive data are correlated. The data can be uncorrelated (white noise), short-range correlated (often called red noise), or long-range correlated (sometimes called pink noise). Here we describe the properties and applications of these different kinds of noise. We discuss, how they influence (i) the diffusion process, (ii) the occurrence of rare extreme events and (iii) the detection of an external trend that is superimposed on the noise; (ii) and (iii) are particularly relevant in the context of detecting anthropogenic global warming by data analysis.
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