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ARTIFICIAL NEURAL NETWORKS

Memristors fire away

Nature Electronicsvolume 1pages100101 (2018) | Download Citation

Neuromorphic computing based on fully memristive neural networks could offer a scalable and lower-cost alternative to existing neural spiking chips based solely on CMOS technology.

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References

  1. 1.

    Indiveri, G. et al. Front. Neurosci. 5, 73 (2011).

  2. 2.

    Bartolozzi, C. et al. Wiley Encycl. Elec. Electron. Eng. https://doi.org/10.1002/047134608X.W8328 (2016).

  3. 3.

    Merolla, P. A. et al. Science 345, 668–673 (2014).

  4. 4.

    Mayberry, M. Intel’s new self-learning chip promises to accelerate artificial intelligence. Intel (25 September 2017).

  5. 5.

    Wang, Z. et al. Nat. Electron. https://doi.org/10.1038/s41928-018-0023-2 (2018).

  6. 6.

    Thorpe, S., Fize, D. & Marlot, C. Nature 381, 520–522 (1996).

  7. 7.

    Hubel, D. H. & Wiesel, T. N. J. Physiol. 148, 574–591 (1959).

  8. 8.

    Chua, L. IEEE Trans. Circuit Theory 18, 507–519 (1971).

  9. 9.

    Strukov, D. B., Snider, G. S., Stewart, D. R. & Williams, R. S. Nature 453, 80–83 (2008).

  10. 10.

    Fujitsu Semiconductor launches world's largest density 4 Mbit ReRAM product for mass production. Fujitsu (26 October 2016).

  11. 11.

    Zamarreño-Ramos, C. et al. Front. Neurosci. 5, 26 (2011).

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Affiliations

  1. Instituto de Microelectronica de Sevilla (IMSE-CNM), CSIC and Universidad de Sevilla, Sevilla, Spain

    • Bernabe Linares-Barranco

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Correspondence to Bernabe Linares-Barranco.

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DOI

https://doi.org/10.1038/s41928-018-0028-x

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