News & Views | Published:

Neuromorphic computation

Sparse codes from memristor grids

Nature Nanotechnology volume 12, pages 722723 (2017) | Download Citation

The adjustable resistive state of memristors makes it possible to implement sparse coding algorithms naturally and efficiently.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    Perception 1, 371–394 (1972).

  2. 2.

    & Nature 381, 607–609 (1996).

  3. 3.

    , & Proc. IEEE 98, 972–982 (2010).

  4. 4.

    et al. Proc. IEEE 98, 1031–1044 (2010).

  5. 5.

    , & in 2011 IEEE Int. Conf. Computer Vision (2011).

  6. 6.

    et al. Nat. Nanotech. 12, 784–789 (2017).

  7. 7.

    , , & Neural Comput. 20, 2526–2563 (2008).

  8. 8.

    , , & IEEE J. Em. Sel. Top. C. 2, 530–541 (2012).

  9. 9.

    et al. Nature 521, 61–64 (2015).

  10. 10.

    , & PLoS Comput. Biol. 7, e1002250 (2011).

Download references

Author information

Affiliations

  1. Bruno A. Olshausen is at Helen Wills Neuroscience Institute and School of Optometry, University of California, Berkeley, California 94720, USA

    • Bruno A. Olshausen
  2. Christopher J. Rozell is in the School of Electrical and Computer Engineering, Georgia Institute of Technology, Georgia 30332, USA

    • Christopher J. Rozell

Authors

  1. Search for Bruno A. Olshausen in:

  2. Search for Christopher J. Rozell in:

Corresponding authors

Correspondence to Bruno A. Olshausen or Christopher J. Rozell.

About this article

Publication history

Published

DOI

https://doi.org/10.1038/nnano.2017.112

Further reading

Find nanotechnology articles, nanomaterial data and patents all in one place. Visit Nano by Nature Research