Evidence map›Paper›PMID 35484107›Full record

ArticleNature communications2022

Implementing in-situ self-organizing maps with memristor crossbar arrays for data mining and optimization.

Rui Wang, Tuo Shi, Xumeng Zhang, Jinsong Wei, Jian Lu, Jiaxue Zhu, Zuheng Wu, Qi Liu, Ming Liu

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Ion Crowding Effect in Unilaterally Downsized Perovskite Memristors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Advances in Metal Halide Perovskite Memristors: A Review from a Co-Design Perspective.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  10. Machine learning without a processor: Emergent learning in a nonlinear analog network.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Memcapacitor Crossbar Array with Charge Trap NAND Flash Structure for Neuromorphic Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  15. Article
  16. Review
  17. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Rui WangThe Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics Chinese Academy of Sciences, 100029, Beijing, PR China.
Tuo ShiThe Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics Chinese Academy of Sciences, 100029, Beijing, PR China. shituo@ime.ac.cn.
Xumeng ZhangThe Frontier institute of Chip and System, Fudan University, 200433, Shanghai, PR China.ORCID http://orcid.org/0000-0002-3828-151X
Jinsong WeiThe Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics Chinese Academy of Sciences, 100029, Beijing, PR China.
Jian LuThe Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics Chinese Academy of Sciences, 100029, Beijing, PR China.
Jiaxue ZhuThe Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics Chinese Academy of Sciences, 100029, Beijing, PR China.
Zuheng WuThe Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics Chinese Academy of Sciences, 100029, Beijing, PR China.
Qi LiuThe Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics Chinese Academy of Sciences, 100029, Beijing, PR China. qi_liu@fudan.edu.cn.ORCID http://orcid.org/0000-0001-7062-831X
Ming LiuThe Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics Chinese Academy of Sciences, 100029, Beijing, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A self-organizing map (SOM) is a powerful unsupervised learning neural network for analyzing high-dimensional data in various applications. However, hardware implementation of SOM is challenging because of the complexity in calculating the similarities and determining neighborhoods. We experimentally demonstrated a memristor-based SOM based on Ta/TaO

Identifiers

PMID35484107
PMCPMC9051161

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.