4 May 2007 Patching Cn2 time series data holes using principal component analysis
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Abstract
Measurements of Cn2 time series using unattended commericial scintillometers over long time intervals inevitably lead to data drop-outs or degraded signals. We present a method using Principal Component Analysis (also known as Karhunen-Loève decomposition) that seeks to correct for these event-induced and mechanically-induced signal degradations. We report on the quality of the correction by examining the Intrinsic Mode Functions generated by Empirical Mode Decomposition.
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Mark P. J. L. Chang, Mark P. J. L. Chang, Haedeh Nazari, Haedeh Nazari, Carlos O. Font, Carlos O. Font, G. Charmaine Gilbreath, G. Charmaine Gilbreath, Eun Oh, Eun Oh, } "Patching Cn2 time series data holes using principal component analysis", Proc. SPIE 6551, Atmospheric Propagation IV, 65510L (4 May 2007); doi: 10.1117/12.724706; https://doi.org/10.1117/12.724706
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