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@ARTICLE{Ziegler:889338,
      author       = {Ziegler, Tobias and Waser, Rainer and Wouters, Dirk J. and
                      Menzel, Stephan},
      title        = {{I}n‐{M}emory {B}inary {V}ector–{M}atrix
                      {M}ultiplication {B}ased on {C}omplementary {R}esistive
                      {S}witches},
      journal      = {Advanced intelligent systems},
      volume       = {2},
      number       = {10},
      issn         = {2640-4567},
      address      = {Weinheim},
      publisher    = {Wiley-VCH Verlag GmbH $\&$ Co. KGaA},
      reportid     = {FZJ-2021-00229},
      pages        = {2070100 -},
      year         = {2020},
      note         = {Cover Picture},
      abstract     = {In article number 2000134, Stephan Menzel and co‐workers
                      explore a computation in‐memory concept for binary
                      vector‐matrix multiplications based on complementary
                      resistive switches. Experimental results on a small‐scale
                      demonstrator are shown and the influence of device
                      variability is investigated. The simulated inference of a
                      1‐layer fully connected binary neural network trained on
                      the MNIST data set resulted in an accuracy of nearly
                      $86\%.$},
      cin          = {PGI-7 / PGI-10 / JARA-FIT},
      ddc          = {620},
      cid          = {I:(DE-Juel1)PGI-7-20110106 / I:(DE-Juel1)PGI-10-20170113 /
                      $I:(DE-82)080009_20140620$},
      pnm          = {524 - Controlling Collective States (POF3-524) / Advanced
                      Computing Architectures $(aca_20190115)$},
      pid          = {G:(DE-HGF)POF3-524 / $G:(DE-Juel1)aca_20190115$},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1002/aisy.202070100},
      url          = {https://juser.fz-juelich.de/record/889338},
}