Hermite-type neural network operators: derivative-informed frameworks for functional neuroimaging and signal processing.
- DOI
- 10.1016/j.neunet.2025.108368
- Published
- 2026 Apr
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2025.108368,
title = {Hermite-type neural network operators: derivative-informed frameworks for functional neuroimaging and signal processing.},
author = {Kadak U},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2025.108368},
url = {https://doi.org/10.1016/j.neunet.2025.108368}
}RIS
TY - JOUR TI - Hermite-type neural network operators: derivative-informed frameworks for functional neuroimaging and signal processing. AU - Kadak U PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2025.108368 UR - https://doi.org/10.1016/j.neunet.2025.108368 ER -
APA
U, K. (2026). Hermite-type neural network operators: derivative-informed frameworks for functional neuroimaging and signal processing.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2025.108368
Source records
- pubmed · retrieved 2026-09-25T22:24:32.049Z