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@INPROCEEDINGS{Carta:905813,
      author       = {Carta, Daniele and Benigni, Andrea},
      title        = {{P}erformance {E}valuation of a {M}issing {D}ata {R}ecovery
                      {A}pproach {B}ased on {C}ompressive {S}ensing},
      reportid     = {FZJ-2022-01033},
      pages        = {1-6},
      year         = {2021},
      abstract     = {In this paper, a Compressive Sensing-based approach is
                      proposed to recover missing data in time series signals. The
                      presented technique is based on the combined application of
                      two mathematical techniques: the Discrete Cosine Transform
                      (DCT) and a $\ell_1$-minimization algorithm. The former
                      allows representing the system under test with reference to
                      a new sparse base, while the latter is one of the possible
                      approaches to solve a Compressive Sensing problem,
                      well-known for the capability of recovering undersampled
                      sparse signals.After presenting the state of the art and the
                      steps characterizing the proposed approach, the recovery
                      performances are tested on real voltage and current Root
                      Mean Square (rms) signals, stored on a database. In
                      particular, the different impact on the recovery of random
                      discontinuous values and wide missing signals is evaluated
                      by means of the Mean Absolute Percentage Error (MAPE).},
      month         = {Sep},
      date          = {2021-09-29},
      organization  = {2021 IEEE 11th International Workshop
                       on Applied Measurements for Power
                       Systems (AMPS), Cagliari (Italy), 29
                       Sep 2021 - 1 Oct 2021},
      cin          = {IEK-10},
      cid          = {I:(DE-Juel1)IEK-10-20170217},
      pnm          = {1123 - Smart Areas and Research Platforms (POF4-112) / 1122
                      - Design, Operation and Digitalization of the Future Energy
                      Grids (POF4-112)},
      pid          = {G:(DE-HGF)POF4-1123 / G:(DE-HGF)POF4-1122},
      typ          = {PUB:(DE-HGF)8},
      pubmed       = {WOS:000783741700030},
      UT           = {WOS:000783741700030},
      doi          = {10.1109/AMPS50177.2021.9586042},
      url          = {https://juser.fz-juelich.de/record/905813},
}