% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@MASTERSTHESIS{Liu:873629,
      author       = {Liu, Tianlin},
      title        = {{H}arnessing {S}low {D}ynamics in {N}euromorphic
                      {C}omputation},
      school       = {Jacobs University Bremen},
      type         = {Masterarbeit},
      reportid     = {FZJ-2020-00872},
      pages        = {53 p.},
      year         = {2019},
      note         = {Master thesis of Tianlin LiuLiu was supported by the FZJ
                      through the project SMARTSTART Computational Neuroscience,
                      DB001423.; Masterarbeit, Jacobs University Bremen, 2019},
      abstract     = {Neuromorphic Computing is a nascent research field in which
                      models and devices are designed to process information by
                      emulating biological neural systems. Thanks to their
                      superior energy efficiency, analog neuromorphic systems are
                      highly promising for embedded, wearable, and implantable
                      systems. However, optimizing neural networks deployed on
                      these systems is challenging. One main challenge is the
                      so-called timescale mismatch: Dynamics of analog circuits
                      tend to be too fast to process real-time sensory inputs. In
                      this thesis, we propose a few working solutions to slow down
                      dynamics of on-chip spiking neural networks. We empirically
                      show that, by harnessing slow dynamics, spiking neural
                      networks on analog neuromorphic systems can gain non-trivial
                      performance boosts on a battery of real-time signal
                      processing tasks.},
      cin          = {INM-6 / IAS-6 / INM-10},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
                      I:(DE-Juel1)INM-10-20170113},
      pnm          = {574 - Theory, modelling and simulation (POF3-574) /
                      Smartstart - SMARTSTART Training Program in Computational
                      Neuroscience (90251)},
      pid          = {G:(DE-HGF)POF3-574 / G:(EU-Grant)90251},
      typ          = {PUB:(DE-HGF)19},
      eprint       = {1905.12116},
      howpublished = {arXiv:1905.12116},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:1905.12116;\%\%$},
      url          = {https://juser.fz-juelich.de/record/873629},
}