HyperPCA: a Powerful Tool to Extract Elemental Maps from Noisy Data Obtained in LIBS Mapping of Materials

@article{Finotello2022HyperPCAAP,
  title={HyperPCA: a Powerful Tool to Extract Elemental Maps from Noisy Data Obtained in LIBS Mapping of Materials},
  author={Riccardo Finotello and Mohamed Tamaazousti and J. B. Sirven},
  journal={ArXiv},
  year={2022},
  volume={abs/2111.15187}
}
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Field theoretical approach for signal detection in nearly continuous positive spectra III: Universal features
TLDR
The Z2-symmetry of the classical action exploiting universality arguments is justified and the superiority of definitions based on complete graphs of large size for data analysis is stressed, to tackle the open issue of a good definition of the covariance matrix for tensorial like data.

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TLDR
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