Kalman filtering with finite-step autocorrelated measurement noise
Download
Full text for this resource is not available from the Research Repository.
Export
Liu, Wei ORCID: 0000-0001-7116-510X, Shi, Peng ORCID: 0000-0001-8218-586X and Zhang, Huiyan ORCID: 0000-0003-3406-8954 (2022) Kalman filtering with finite-step autocorrelated measurement noise. Journal of Computational and Applied Mathematics, 408. ISSN 0377-0427
Dimensions Badge
Altmetric Badge
Item type | Article |
URI | https://vuir.vu.edu.au/id/eprint/46647 |
DOI | 10.1016/j.cam.2022.114138 |
Official URL | https://www.sciencedirect.com/science/article/abs/... |
Subjects | Current > FOR (2020) Classification > 4602 Artificial intelligence Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
Keywords | Kalman filtering, discrete time linear systems, convergence behaviour |
Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)