Variable knot-based spline approximation recursive Bayesian algorithm for the identification of Wiener systems with process noise

DOI10.1007/s11071-017-3803-8zbMath1393.93031OpenAlexW2758568103MaRDI QIDQ1663702

Tianhong Pan, Shaoxue Jing, Zheng-ming Li

Publication date: 22 August 2018

Published in: Nonlinear Dynamics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11071-017-3803-8

zbMATH Keywords

parameter estimationprocess noisevariable knotsspline function approximation

Mathematics Subject Classification ID

Dynamical systems in fluid mechanics, oceanography and meteorology (37N10) System identification (93B30) Identification in stochastic control theory (93E12) Spline approximation (41A15)

Related Items (3)

Robust hierarchical identification of Wiener systems in the presence of dynamic disturbances ⋮ Identification of Wiener model with internal noise using a cubic spline approximation-Bayesian composite quantile regression algorithm ⋮ Parameter estimation for a special class of nonlinear systems by using the over-parameterisation method and the linear filter

Cites Work

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