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@INPROCEEDINGS{Yang:1050577,
      author       = {Yang, Ming-Jay and Nieters, Pascal and Hellwig, Johannes
                      and Spithouris, Dimitrios and Dittmann, Regina and Pipa,
                      Gordon and Strachan, John Paul},
      title        = {{B}iologically {I}nspired {M}ulti-{T}imescale {S}equence
                      {P}rocessing in {H}ybrid {CMOS}-{M}emristive {H}ardware},
      publisher    = {IEEE},
      reportid     = {FZJ-2026-00334},
      pages        = {1-4},
      year         = {2025},
      comment      = {2025 32nd IEEE International Conference on Electronics,
                      Circuits and Systems (ICECS) : [Proceedings] - IEEE, 2025. -
                      ISBN 979-8-3315-9585-2 -
                      doi:10.1109/ICECS66544.2025.11270719},
      booktitle     = {2025 32nd IEEE International
                       Conference on Electronics, Circuits and
                       Systems (ICECS) : [Proceedings] - IEEE,
                       2025. - ISBN 979-8-3315-9585-2 -
                       doi:10.1109/ICECS66544.2025.11270719},
      abstract     = {emporal sequences of spiking activity are a primary means
                      of neural information encoding, making the extraction of
                      their structure a fundamental computational challenge in
                      neuroscience and artificial intelligence. Recent advances in
                      neuroscience have introduced the concept of dendritic
                      plateau computation (DPC), a mechanism that emerges from the
                      interaction of localized plateau potentials across
                      functionally compartmentalized dendritic branches. Inspired
                      by this biological paradigm, we propose a memristive
                      dendritic architecture incorporating a multi-compartmental
                      neuron model. Critical sequence features are encoded through
                      tunable resistances at memristive crosspoints, while the
                      adjustable retention time of volatile memristors is utilized
                      to modulate plateau duration, thereby aligning temporal
                      dynamics with application-specific requirements. With the
                      memristive hardware dendrite, we constructed a two-layer
                      network of neuron populations for sequence classification.
                      This work demonstrates the potential advantage of
                      incorporating the active dendritic processes as fundamental
                      operation for implementing efficient brain-inspired
                      computing hardware.},
      month         = {Nov},
      date          = {2025-11-17},
      organization  = {2025 32nd IEEE International
                       Conference on Electronics, Circuits and
                       Systems (ICECS), Marrakech (Morocco),
                       17 Nov 2025 - 19 Nov 2025},
      cin          = {PGI-14},
      cid          = {I:(DE-Juel1)PGI-14-20210412},
      pnm          = {5234 - Emerging NC Architectures (POF4-523) / DFG project
                      G:(GEPRIS)441959088 - Memristiver Zeitabstandskodierer
                      (MemTDE) (441959088)},
      pid          = {G:(DE-HGF)POF4-5234 / G:(GEPRIS)441959088},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      doi          = {10.1109/ICECS66544.2025.11270719},
      url          = {https://juser.fz-juelich.de/record/1050577},
}