Solving Constrained Pseudoconvex Optimization Problems with deep learning-based neurodynamic optimization
- DOI
- 10.1016/j.matcom.2023.12.032
- Published
- 2024-05
- Container
- Mathematics and Computers in Simulation
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.matcom.2023.12.032,
title = {Solving Constrained Pseudoconvex Optimization Problems with deep learning-based neurodynamic optimization},
author = {Dawen Wu and Abdel Lisser},
year = {2024},
journal = {Mathematics and Computers in Simulation},
doi = {10.1016/j.matcom.2023.12.032},
url = {https://doi.org/10.1016/j.matcom.2023.12.032}
}RIS
TY - JOUR TI - Solving Constrained Pseudoconvex Optimization Problems with deep learning-based neurodynamic optimization AU - Dawen Wu AU - Abdel Lisser PY - 2024 JO - Mathematics and Computers in Simulation DO - 10.1016/j.matcom.2023.12.032 UR - https://doi.org/10.1016/j.matcom.2023.12.032 ER -
APA
Wu, D., & Lisser, A. (2024). Solving Constrained Pseudoconvex Optimization Problems with deep learning-based neurodynamic optimization. Mathematics and Computers in Simulation. https://doi.org/10.1016/j.matcom.2023.12.032
Source records
- crossref · retrieved 2026-11-10T20:59:30.708Z