Резултати
eNauka >
Results >
Stability of Gated Recurrent Unit Neural Networks: Convex Combination Formulation Approach
| Title: | Stability of Gated Recurrent Unit Neural Networks: Convex Combination Formulation Approach | Authors: | Stipanović, Dušan; Kapetina, Mirna   ; Rapaić, Milan ; Murmann, Boris |
Issue Date: | 2021 | Publication: | Journal of Optimization Theory and Applications | ISSN: | 0022-3239 Journal of Optimization Theory and Applications Search Idenfier |
Type: | Article | Collation: | vol. 188 br. 1 str. 291-306 | DOI: | 10.1007/s10957-020-01776-w | WoS-ID: | 000587127400001 | Scopus-ID: | 2-s2.0-85095415489 | URI: | https://enauka.gov.rs/handle/123456789/797040 | Project: | National Robotics Initiative grant titled "NRI: FND: COLLAB: Multi-Vehicle Systems for Collecting Shadow-Free Imagery in Precision Agriculture" from the USDA National Institute of Food and Agriculture [2019-04791, 1020285] Serbian Ministry of Education, |
Metadata source: | (Preuzeto iz Nasi u WoS) | M-category: | 21M21 |
3
SCOPUSTM
7
WEB OF SCIENCETM
Алт метрика
Dimensions
Unpaywall
Резултати на еНаука су заштићени ауторским правима и сва права су задржана, осим ако није другачије назначено.