Gradient-based recursive parameter estimation for a periodically nonuniformly sampled-data Hammerstein-Wiener system based on the key-term separation
From MaRDI portal
Publication:6494842
DOI10.1002/ACS.3296MaRDI QIDQ6494842
Publication date: 30 April 2024
Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)
hierarchical identification principleHammerstein-Wiener modelkey-term separationgradient searchnonuniform sampling
Cites Work
- Parameter estimation with scarce measurements
- Auxiliary model based multi-innovation stochastic gradient identification algorithm for periodically non-uniformly sampled-data Hammerstein systems
- A unified approach for the parametric identification of SISO/MIMO Wiener and Hammerstein systems
- 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
- Identification of Hammerstein-Wiener models
- A numerical solution of a class of periodic coupled matrix equations
- 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
- Fully parametric identification for continuous time fractional order Hammerstein systems
- Recursive identification of bilinear time-delay systems through the redundant rule
- Adaptive filtering-based recursive identification for time-varying Wiener output-error systems with unknown noise statistics
- Nonlinear system identification using fractional Hammerstein-Wiener models
- Switch detection and robust parameter estimation for slowly switched Hammerstein systems
- Hierarchical recursive generalized extended least squares estimation algorithms for a class of nonlinear stochastic systems with colored noise
- Identification of a modified Wiener-Hammerstein system and its application in electrically stimulated paralyzed skeletal muscle modeling
- Particle filtering based parameter estimation for systems with output-error type model structures
- Output feedback stabilization for Markov-based nonuniformly sampled-data networked control systems
- A Regularized Variable Projection Algorithm for Separable Nonlinear Least Squares Problems
- 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
- 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
- Separable multi‐innovation stochastic gradient estimation algorithm for the nonlinear dynamic responses of systems
- Hierarchical parameter and state estimation for bilinear systems
- Bayesian approach to identify Hammerstein–Wiener non‐linear model in presence of noise and disturbance
- Highly computationally efficient state filter based on the delta operator
- 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
- Decomposition-based recursive least-squares parameter estimation algorithm for Wiener-Hammerstein systems with dead-zone nonlinearity
- State and parameter joint estimation of linear stochastic systems in presence of faults and <scp>non‐Gaussian</scp> noises
- Decomposition‐based over‐parameterization forgetting factor stochastic gradient algorithm for Hammerstein‐Wiener nonlinear systems with non‐uniform sampling
- 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
This page was built for publication: Gradient-based recursive parameter estimation for a periodically nonuniformly sampled-data Hammerstein-Wiener system based on the key-term separation