Neuromorphic function learning with carbon nanotube based synapses.

@article{Gacem2013NeuromorphicFL,
  title={Neuromorphic function learning with carbon nanotube based synapses.},
  author={Karim Gacem and Jean-Marie Retrouvey and Djaafar Chabi and Arianna Filoramo and Weisheng Zhao and Jacques-Olivier Klein and Vincent Derycke},
  journal={Nanotechnology},
  year={2013},
  volume={24 38},
  pages={
          384013
        }
}
The principle of using nanoscale memory devices as artificial synapses in neuromorphic circuits is recognized as a promising way to build ground-breaking circuit architectures tolerant to defects and variability. Yet, actual experimental demonstrations of the neural network type of circuits based on non-conventional/non-CMOS memory devices and displaying function learning capabilities remain very scarce. We show here that carbon-nanotube-based memory elements can be used as artificial synapses… CONTINUE READING

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