Patching C2n Time Series Data Holes using Principal Component Analysis

Abstract

Measurements of C2n time series using unattended commercial 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-Loeve 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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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2007
Accession Number
ADA472217

Entities

People

  • Carlos O. Font
  • Eun Oh
  • G. Charmaine Gilbreath
  • Haedeh Nazari
  • Mark P. Chang

Organizations

  • United States Naval Research Laboratory

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Data Analysis
  • Data Science
  • Data Sets
  • Decomposition
  • Eigenvalues
  • Eigenvectors
  • Factor Analysis
  • Information Science
  • Intervals
  • Measurement
  • Measuring Instruments
  • Military Research
  • Puerto Rico
  • Standards
  • Time Intervals
  • Turbulence

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Educational Psychology
  • Image Processing and Computer Vision.