4 May 2007 Patching Cn2 time series data holes using principal component analysis
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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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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