Evidence map›Paper›PMID 38745045›Full record

ArticleScientific reports2024

Highly-integrable analogue reservoir circuits based on a simple cycle architecture.

Yuki Abe, Kazuki Nakada, Naruki Hagiwara, Eiji Suzuki, Keita Suda, Shin-Ichiro Mochizuki, Yukio Terasaki, Tomoyuki Sasaki, Tetsuya Asai

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Yuki AbeGraduate School of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo, Hokkaido, 0600814, Japan.
Kazuki NakadaAdvanced Products Development Center, Technology and Intellectual Property HQ, TDK Corporation, 2-15-17 Higashi-Owada, Ichikawa, Chiba, 2728558, Japan.
Naruki HagiwaraGraduate School of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo, Hokkaido, 0600814, Japan.
Eiji SuzukiAdvanced Products Development Center, Technology and Intellectual Property HQ, TDK Corporation, 2-15-17 Higashi-Owada, Ichikawa, Chiba, 2728558, Japan.
Keita SudaAdvanced Products Development Center, Technology and Intellectual Property HQ, TDK Corporation, 2-15-17 Higashi-Owada, Ichikawa, Chiba, 2728558, Japan.
Shin-Ichiro MochizukiAdvanced Products Development Center, Technology and Intellectual Property HQ, TDK Corporation, 2-15-17 Higashi-Owada, Ichikawa, Chiba, 2728558, Japan.
Yukio TerasakiAdvanced Products Development Center, Technology and Intellectual Property HQ, TDK Corporation, 2-15-17 Higashi-Owada, Ichikawa, Chiba, 2728558, Japan.
Tomoyuki SasakiAdvanced Products Development Center, Technology and Intellectual Property HQ, TDK Corporation, 2-15-17 Higashi-Owada, Ichikawa, Chiba, 2728558, Japan.
Tetsuya AsaiFaculty of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo, Hokkaido, 0600814, Japan. asai@ist.hokudai.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Physical reservoir computing is a promising solution for accelerating artificial intelligence (AI) computations. Various physical systems that exhibit nonlinear and fading-memory properties have been proposed as physical reservoirs. Highly-integrable physical reservoirs, particularly for edge AI computing, has a strong demand. However, realizing a practical physical reservoir with high performance and integrability remains challenging. Herein, we present an analogue circuit reservoir with a simple cycle architecture suitable for complementary metal-oxide-semiconductor (CMOS) chip integration. In several benchmarks and demonstrations using synthetic and real-world data, our developed hardware prototype and its simulator exhibit a high prediction performance and sufficient memory capacity for practical applications, showing promise for future applications in highly integrated AI accelerators.

Indexed as

Analogue circuitChaos predictionEdge computingPhysical reservoir computing

Identifiers

PMID38745045
PMCPMC11094067

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.