@inproceedings{petrovici_arxiv2017,
  title = {Pattern representation and recognition with accelerated analog neuromorphic systems},
  url = {http://arxiv.org/abs/1703.06043},
  urldate = {2017-06-10},
  booktitle = {{arXiv}:1703.06043 [cs, q-bio, stat]},
  author = {Petrovici, Mihai A. and Schmitt, Sebastian and Klähn, Johann and Stöckel, David and Schroeder, Anna and Bellec, Guillaume and Bill, Johannes and Breitwieser, Oliver and Bytschok, Ilja and Grübl, Andreas and Güttler, Maurice and Hartel, Andreas and Hartmann, Stephan and Husmann, Dan and Husmann, Kai and Jeltsch, Sebastian and Karasenko, Vitali and Kleider, Mitja and Koke, Christoph and Kononov, Alexander and Mauch, Christian and Müller, Paul and Partzsch, Johannes and Pfeil, Thomas and Schiefer, Stefan and Scholze, Stefan and Subramoney, Anand and Thanasoulis, Vasilis and Vogginger, Bernhard and Legenstein, Robert and Maass, Wolfgang and Schüffny, René and Mayr, Christian and Schemmel, Johannes and Meier, Karlheinz},
  month = mar,
  year = {2017},
  note = {arXiv: 1703.06043},
  keywords = {Neuromorphics, Quantitative Biology - Neurons and Cognition, Statistics - Machine Learning, Neurons, Computer Science - Neural and Evolutionary Computing, artificial neural networks, neural net architecture, Training, accelerated analog neuromorphic systems, analog components, analogue circuits, auxiliary network, biological archetypes, Biomembranes, central nervous system, fast low-power neuromorphic hardware, Hardware, hardware-emulated networks, low-power electronics, neural chips, pattern recognition, pattern representation, realistic spiking networks, Robustness, system dynamics}
}