Data filtering-based multi-innovation stochastic gradient algorithm for nonlinear output error autoregressive systems

DOI10.1007/s00034-015-0064-yzbMath1346.93188OpenAlexW835816250MaRDI QIDQ308042

Feng Ding, Yawen Mao

Publication date: 5 September 2016

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

Full work available at URL: https://doi.org/10.1007/s00034-015-0064-y

zbMATH Keywords

nonlinear systemmulti-innovation identification theorystochastic gradientdata filtering technique

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Identification in stochastic control theory (93E12)

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A novel parameter separation based identification algorithm for Hammerstein systems ⋮ A recursive least squares algorithm for pseudo-linear ARMA systems using the auxiliary model and the filtering technique ⋮ Auxiliary model-based iterative estimation algorithms for nonlinear systems using the covariance matrix adaptation strategy ⋮ Parameter estimation for nonlinear systems by using the data filtering and the multi-innovation identification theory ⋮ Design of normalized fractional adaptive algorithms for parameter estimation of control autoregressive autoregressive systems ⋮ Recursive least squares identification methods for multivariate pseudo-linear systems using the data filtering

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