Authors: Berke, Olaf
Title: Filtering the Noise from Time Series and Spatial Data
Language (ISO): en
Abstract: Noisy observations form the basis for almost every scientific research and especially in environmental monitoring. The Noise is often an effect of imprecise instruments which cause measurement errors. If the noise variance is known it is possible to filter out the contaminating noise from the observations and then to predict the latent signal process. Solutions for this problem exist for time series application and will be briefly reviewed. In the geostatistical literature, i.e. for the analysis of spatial data, similar methods have been foreshadowed in the literature and will be outlined in this work.
Subject Headings: geostatistics
Kalman Filter
kriging
prediction
signal
time series analysis
URI: http://hdl.handle.net/2003/4881
http://dx.doi.org/10.17877/DE290R-14542
Issue Date: 1998
Publisher: Universitätsbibliothek Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 475

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