A recursive least squares algorithm for pseudo-linear ARMA systems using the auxiliary model and the filtering technique

DOI10.1007/s00034-015-0164-8zbMath1346.93406OpenAlexW1835518436MaRDI QIDQ318271

Lanjie Guo, Yanjiao Wang, Cheng Wang

Publication date: 4 October 2016

Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00034-015-0164-8

zbMATH Keywords

parameter estimationleast squaresauxiliary modeldata filteringpseudo-linear system

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10) Least squares and related methods for stochastic control systems (93E24) Software, source code, etc. for problems pertaining to systems and control theory (93-04)

Related Items (5)

Coupled least squares identification algorithms for multivariate output-error systems ⋮ Adaptive filtering scheme for parameter identification of nonlinear Wiener–Hammerstein systems and its application ⋮ New gradient based identification methods for multivariate pseudo-linear systems using the multi-innovation and the data filtering ⋮ Variational Bayesian-based iterative algorithm for ARX models with random missing outputs ⋮ Recursive least-squares algorithm for a characteristic model with coloured noise by means of the data filtering technique

Uses Software

• System Identification Toolbox

Cites Work

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