Exploiting Intrinsic Variability of Filamentary Resistive Memory for Extreme Learning Machine Architectures

@article{Suri2015ExploitingIV,
  title={Exploiting Intrinsic Variability of Filamentary Resistive Memory for Extreme Learning Machine Architectures},
  author={Manan Suri and Vivek Parmar},
  journal={IEEE Transactions on Nanotechnology},
  year={2015},
  volume={14},
  pages={963-968}
}
In this paper, we show for the first time how unavoidable device variability of emerging nonvolatile resistive memory devices can be exploited to design efficient low-power, low-footprint extreme learning machine (ELM) architectures. In particular, we utilize the uncontrollable off-state resistance (Roff/HRS) spreads, of nanoscale filamentary-resistive memory devices, to realize random input weights and random hidden neuron biases; a characteristic requirement of ELM. We propose a novel RRAM… CONTINUE READING
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