Partial-encryption-decryption-based secure state estimation of singularly perturbed complex networks: A Paillier encryption approach.
- DOI
- 10.1016/j.neunet.2026.109292
- Published
- 2026 Dec
- 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.2026.109292,
title = {Partial-encryption-decryption-based secure state estimation of singularly perturbed complex networks: A Paillier encryption approach.},
author = {Chen Y and Wang Z and Liu Y and Song W},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.109292},
url = {https://doi.org/10.1016/j.neunet.2026.109292}
}RIS
TY - JOUR TI - Partial-encryption-decryption-based secure state estimation of singularly perturbed complex networks: A Paillier encryption approach. AU - Chen Y AU - Wang Z AU - Liu Y AU - Song W PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.109292 UR - https://doi.org/10.1016/j.neunet.2026.109292 ER -
APA
Y, C., Z, W., Y, L., & W, S. (2026). Partial-encryption-decryption-based secure state estimation of singularly perturbed complex networks: A Paillier encryption approach.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.109292
Source records
- pubmed · retrieved 2026-09-25T20:12:07.048Z