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@ARTICLE{Huang:864467,
      author       = {Huang, Xiaolei and Dong, Hui and Tao, Quan and Yu, Mengmeng
                      and Li, Yongqiang and Rong, Liangliang and Krause,
                      Hans-Joachim and Offenhäusser, Andreas and Xie, Xiaoming},
      title        = {{S}ensor {C}onfiguration and {A}lgorithms for
                      {P}ower-{L}ine {I}nterference {S}uppression in {L}ow {F}ield
                      {N}uclear {M}agnetic {R}esonance},
      journal      = {Sensors},
      volume       = {19},
      number       = {16},
      issn         = {1424-8220},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2019-04248},
      pages        = {3566 -},
      year         = {2019},
      abstract     = {Low field (LF) nuclear magnetic resonance (NMR) shows
                      potential advantages to study pure heteronuclear J-coupling
                      and observe the fine structure of matter. Power-line
                      harmonics interferences and fixed-frequency noise peaks
                      might introduce discrete noise peaks into the LF-NMR
                      spectrum in an open environment or in a conductively
                      shielded room, which might disturb J-coupling spectra of
                      matter recorded at LF. In this paper, we describe a
                      multi-channel sensor configuration of superconducting
                      quantum interference devices, and measure the multiple peaks
                      of the 2,2,2-trifluoroethanol J-coupling spectrum. For the
                      case of low signal to noise ratio (SNR) < 1, we suggest two
                      noise suppression algorithms using discrete wavelet analysis
                      (DWA), combined with either least squares method (LSM) or
                      gradient descent (GD). The de-noising methods are based on
                      spatial correlation of the interferences among the
                      superconducting sensors, and are experimentally
                      demonstrated. The DWA-LSM algorithm shows a significant
                      effect in the noise reduction and recovers SNR > 1 for most
                      of the signal peaks. The DWA-GD algorithm improves the SNR
                      further, but takes more computational time. Depending on
                      whether the accuracy or the speed of the de-noising process
                      is more important in LF-NMR applications, the choice of
                      algorithm should be made},
      cin          = {ICS-8},
      ddc          = {620},
      cid          = {I:(DE-Juel1)ICS-8-20110106},
      pnm          = {523 - Controlling Configuration-Based Phenomena (POF3-523)},
      pid          = {G:(DE-HGF)POF3-523},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31443310},
      UT           = {WOS:000484407200123},
      doi          = {10.3390/s19163566},
      url          = {https://juser.fz-juelich.de/record/864467},
}