Parameter tracking of time-varying Hammerstein-Wiener systems
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Publication:5029102
DOI10.1080/00207721.2021.1931546zbMath1483.93639OpenAlexW3172005832MaRDI QIDQ5029102
Publication date: 11 February 2022
Published in: International Journal of Systems Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207721.2021.1931546
Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10) Linear systems in control theory (93C05) Identification in stochastic control theory (93E12)
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Cites Work
- The recursive least squares identification algorithm for a class of Wiener nonlinear systems
- Adaptation and tracking in system identification - a survey
- An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems
- A blind approach to the Hammerstein-Wiener model identification
- Identification of nonlinear dynamic systems with input saturation and output backlash using three-block cascade models
- Variational Bayesian approach for ARX systems with missing observations and varying time-delays
- Identification of Hammerstein-Wiener models
- Frequency identification of nonparametric Wiener systems containing backlash nonlinearities
- Modified Kalman filtering based multi-step-length gradient iterative algorithm for ARX models with random missing outputs
- Problems of identification and control
- Fluctuation analysis of stochastic gradient identification of polynomial Wiener systems
- System identification of Wiener systems with B-spline functions using De Boor recursion
- Modelling and control of Hammerstein system using B-spline approximation and the inverse of De Boor algorithm
- Stochastic stability of the discrete-time extended Kalman filter
- Two-stage multi-innovation stochastic gradient algorithm for multivariate output-error ARMA systems based on the auxiliary model
- Two-step output feedback predictive control for Hammerstein systems with networked-induced time delays
- Recursive Identification of MIMO Wiener Systems
- Recursive identification of Hammerstein systems with dead-zone nonlinearity in the presence of bounded noise
- Decomposition-based recursive least-squares parameter estimation algorithm for Wiener-Hammerstein systems with dead-zone nonlinearity
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