VLSI Extreme Learning Machine: A Design Space Exploration

@article{Yao2017VLSIEL,
  title={VLSI Extreme Learning Machine: A Design Space Exploration},
  author={Enyi Yao and Arindam Basu},
  journal={IEEE Transactions on Very Large Scale Integration (VLSI) Systems},
  year={2017},
  volume={25},
  pages={60-74}
}
In this paper, we describe a compact low-power high-performance hardware implementation of extreme learning machine for machine learning applications. Mismatches in current mirrors are used to perform the vector-matrix multiplication that forms the first stage of this classifier and is the most computationally intensive. Both regression and classification (on UCI data sets) are demonstrated and a design space tradeoff between speed, power, and accuracy is explored. Our results indicate that for… CONTINUE READING
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http://archive.ic s.uci.edu/ml

  • UCI Machine Learning repository
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Computati on using Mismatch: Neuromorphic Extreme Learning Machines

  • Y. Enyi, S. Hussain, A. Basu, G. B. Huang
  • Proceedings of the IEEE Biomedical Circuits and…
  • 2013
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