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Identifying presence of correlated errors using machine learning algorithms for the selective de-correlation of GRACE harmonic coefficients

Piretzidis, D., Sra, G., Karantaidis, G., Sideris, M. G., and Kabirzadeh, H., 2018. Identifying presence of correlated errors using machine learning algorithms for the selective de-correlation of GRACE harmonic coefficients. Geophysical Journal International, 215:375–388, doi:10.1093/gji/ggy272.

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BibTeX

@ARTICLE{2018GeoJI.215..375P,
   author = {{Piretzidis}, D. and {Sra}, G. and {Karantaidis}, G. and {Sideris}, M.~G. and {Kabirzadeh}, H.},
    title = "{Identifying presence of correlated errors using machine learning algorithms for the selective de-correlation of GRACE harmonic coefficients}",
  journal = {Geophysical Journal International},
 keywords = {GRACE satellite, Spherical harmonics, Correlated errors, Machine learning, Mass changes},
     year = 2018,
    month = oct,
   volume = 215,
    pages = {375-388},
      doi = {10.1093/gji/ggy272},
   adsurl = {http://adsabs.harvard.edu/abs/2018GeoJI.215..375P},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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