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Open-loop analog programmable electrochemical memory array

Author

Listed:
  • Peng Chen

    (Zhejiang University)

  • Fenghao Liu

    (Zhejiang University)

  • Peng Lin

    (Zhejiang University
    Zhejiang University)

  • Peihong Li

    (Zhejiang University)

  • Yu Xiao

    (Zhejiang University)

  • Bihua Zhang

    (Zhejiang University)

  • Gang Pan

    (Zhejiang University
    Zhejiang University)

Abstract

Emerging memories have been developed as new physical infrastructures for hosting neural networks owing to their low-power analog computing characteristics. However, accurately and efficiently programming devices in an analog-valued array is still largely limited by the intrinsic physical non-idealities of the devices, thus hampering their applications in in-situ training of neural networks. Here, we demonstrate a passive electrochemical memory (ECRAM) array with many important characteristics necessary for accurate analog programming. Different image patterns can be open-loop and serially programmed into our ECRAM array, achieving high programming accuracies without any feedback adjustments. The excellent open-loop analog programmability has led us to in-situ train a bilayer neural network and reached software-like classification accuracy of 99.4% to detect poisonous mushrooms. The training capability is further studied in simulation for large-scale neural networks such as VGG-8. Our results present a new solution for implementing learning functions in an artificial intelligence hardware using emerging memories.

Suggested Citation

  • Peng Chen & Fenghao Liu & Peng Lin & Peihong Li & Yu Xiao & Bihua Zhang & Gang Pan, 2023. "Open-loop analog programmable electrochemical memory array," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41958-4
    DOI: 10.1038/s41467-023-41958-4
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