Study on analog circuit implementation of ReLU Hopfield Neural Network for inequality-constrained optimization problems.

Okubo R, Mitsuya Y, Takahashi H

DOI: 10.3389/fnins.2026.1885313
Published: 2026
Container: Frontiers in neuroscience
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fnins.2026.1885313,
  title = {Study on analog circuit implementation of ReLU Hopfield Neural Network for inequality-constrained optimization problems.},
  author = {Okubo R and Mitsuya Y and Takahashi H},
  year = {2026},
  journal = {Frontiers in neuroscience},
  doi = {10.3389/fnins.2026.1885313},
  url = {https://doi.org/10.3389/fnins.2026.1885313}
}

RIS

TY  - JOUR
TI  - Study on analog circuit implementation of ReLU Hopfield Neural Network for inequality-constrained optimization problems.
AU  - Okubo R
AU  - Mitsuya Y
AU  - Takahashi H
PY  - 2026
JO  - Frontiers in neuroscience
DO  - 10.3389/fnins.2026.1885313
UR  - https://doi.org/10.3389/fnins.2026.1885313
ER  -

APA

R, O., Y, M., & H, T. (2026). Study on analog circuit implementation of ReLU Hopfield Neural Network for inequality-constrained optimization problems.. Frontiers in neuroscience. https://doi.org/10.3389/fnins.2026.1885313

Source records

pubmed · retrieved 2026-09-25T17:55:57.751Z