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Neuromorphic computation

Sparse codes from memristor grids

Nature Nanotechnology volume 12, pages 722–723 (2017)Cite this article

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

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Figure 1: Sparse coding of an image.

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Author information

Authors and 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. Bruno A. Olshausen
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  2. Christopher J. Rozell
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Correspondence to Bruno A. Olshausen or Christopher J. Rozell.

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Olshausen, B., Rozell, C. Sparse codes from memristor grids. Nature Nanotech 12, 722–723 (2017). https://doi.org/10.1038/nnano.2017.112

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