Decomposition‐based over‐parameterization forgetting factor stochastic gradient algorithm for Hammerstein‐Wiener nonlinear systems with non‐uniform sampling
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Publication:6060476
DOI10.1002/rnc.5576zbMath1525.93439OpenAlexW3168606244MaRDI QIDQ6060476
Qi-lin Liu, Yongsong Xiao, Feng Ding, Tasawar Hayat
Publication date: 3 November 2023
Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/rnc.5576
parameter estimationnonlinear systemdecomposition techniqueHammerstein-Wiener modelover-parameterization
Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10)
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Cites Work
- The expected discounted penalty function under a renewal risk model with stochastic income
- Gradient iterative algorithm for dual-rate nonlinear systems based on a novel particle filter
- Data-driven recursive least squares methods for non-affined nonlinear discrete-time systems
- On spectrally positive Lévy risk processes with Parisian implementation delays in dividend payments
- Spectrally negative Lévy risk model under Erlangized barrier strategy
- State space model identification of multirate processes with time-delay using the expectation maximization
- Moving horizon estimation for multirate systems with time-varying time-delays
- A numerical solution of a class of periodic coupled matrix equations
- Piecewise reproducing kernel-based symmetric collocation approach for linear stationary singularly perturbed problems
- Hierarchical least squares parameter estimation algorithm for two-input Hammerstein finite impulse response systems
- A recursive parameter estimation algorithm for modeling signals with multi-frequencies
- An finite iterative algorithm for sloving periodic Sylvester bimatrix equations
- Reproducing kernel function-based Filon and Levin methods for solving highly oscillatory integral
- A recursive identification algorithm for Wiener nonlinear systems with linear state-space subsystem
- Hierarchical recursive generalized extended least squares estimation algorithms for a class of nonlinear stochastic systems with colored noise
- Optimal periodic dividend and capital injection problem for spectrally positive Lévy processes
- An extension of Paulsen-Gjessing's risk model with stochastic return on investments
- Partially Coupled Stochastic Gradient Identification Methods for Non-Uniformly Sampled Systems
- Two‐stage auxiliary model gradient‐based iterative algorithm for the input nonlinear controlled autoregressive system with variable‐gain nonlinearity
- Adaptive parameter estimation for a general dynamical system with unknown states
- Recursive parameter estimation methods and convergence analysis for a special class of nonlinear systems
- Decomposition‐based multiinnovation gradient identification algorithms for a special bilinear system based on its input‐output representation
- Parameter estimation for block‐oriented nonlinear systems using the key term separation
- A robust least squares based approach to min‐max model predictive control
- Wiener system identification by input injection method
- Hierarchical Newton and least squares iterative estimation algorithm for dynamic systems by transfer functions based on the impulse responses
- Recursive Gauss–Seidel algorithm for direct self‐tuning control
- Highly computationally efficient state filter based on the delta operator
- State estimation for bilinear systems through minimizing the covariance matrix of the state estimation errors
- The filtering‐based maximum likelihood iterative estimation algorithms for a special class of nonlinear systems with autoregressive moving average noise using the hierarchical identification principle
- Three‐stage forgetting factor stochastic gradient parameter estimation methods for a class of nonlinear systems
- Maximum likelihood extended gradient‐based estimation algorithms for the input nonlinear controlled autoregressive moving average system with variable‐gain nonlinearity
- Auxiliary model multiinnovation stochastic gradient parameter estimation methods for nonlinear sandwich systems
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