Maximum likelihood gradient‐based iterative estimation for multivariable systems

DOI10.1049/iet-cta.2018.6240zbMath1432.93329OpenAlexW2936333535WikidataQ127990074 ScholiaQ127990074MaRDI QIDQ5221136

Ling Xu, Feng Ding, Huafeng Xia, Yongqing Yang, Tasawar Hayat

Publication date: 24 March 2020

Published in: IET Control Theory & Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1049/iet-cta.2018.6240

Mathematics Subject Classification ID

Point estimation (62F10) Estimation and detection in stochastic control theory (93E10)

Related Items (4)

Multi‐innovation gradient parameter estimation for multivariable systems based on the maximum likelihood principle ⋮ Instrumental variable‐based multi‐innovation gradient estimation for nonlinear systems with scarce measurements ⋮ An efficient conjugate gradient based Cholesky CMA‐ES estimation algorithm for nonlinear systems ⋮ Maximum likelihood iterative identification approaches for multivariable equation-error moving average systems

This page was built for publication: Maximum likelihood gradient‐based iterative estimation for multivariable systems