Data filtering-based multi-innovation forgetting gradient algorithms for input nonlinear FIR-MA systems with piecewise-linear characteristics
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Publication:2068227
DOI10.1016/j.jfranklin.2021.10.001zbMath1480.93084OpenAlexW3206253124MaRDI QIDQ2068227
Publication date: 19 January 2022
Published in: Journal of the Franklin Institute (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jfranklin.2021.10.001
Related Items (4)
Data filtering‐based parameter estimation algorithms for a class of nonlinear systems with colored noises ⋮ A novel hybrid filter-based fault diagnosis algorithm for switched systems with a dual noise term ⋮ Tuning-free filtering for stochastic systems with unmodeled measurement dynamics ⋮ Filtering-based gradient joint identification algorithms for nonlinear fractional-order models with colored noises
Cites Work
- Novel data filtering based parameter identification for multiple-input multiple-output systems using the auxiliary model
- Parameter estimation with scarce measurements
- Data filtering based maximum likelihood gradient estimation algorithms for a multivariate equation-error system with ARMA noise
- A hierarchical least squares identification algorithm for Hammerstein nonlinear systems using the key term separation
- Consistency of the robust recursive Hammerstein model identification algorithm
- Combined state and parameter estimation for a bilinear state space system with moving average noise
- Recursive parameter identification of the dynamical models for bilinear state space 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
- Robust fault tolerant tracking control for the multi-joint manipulator based on operator theory
- Hierarchical least squares identification for feedback nonlinear equation-error systems
- Hierarchical gradient- and least squares-based iterative algorithms for input nonlinear output-error systems using the key term separation
- 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
- Hierarchical extended least squares estimation approaches for a multi-input multi-output stochastic system with colored noise from observation data
- Partially-coupled nonlinear parameter optimization algorithm for a class of multivariate hybrid models
- Recursive identification of bilinear time-delay systems through the redundant rule
- Hierarchical recursive generalized extended least squares estimation algorithms for a class of nonlinear stochastic systems with colored noise
- Recursive least squares and multi-innovation stochastic gradient parameter estimation methods for signal modeling
- Identification of Wiener-Hammerstein systems by a nonparametric separation of the best linear approximation
- Robust Kalman filtering for nonlinear multivariable stochastic systems in the presence of non-Gaussian noise
- Parameter identification of linear multi-delay systems via a hybrid of block-pulse functions and Taylor’s polynomials
- Real‐time identification of nonlinear multiple‐input–multiple‐output systems with unknown input time delay using Wiener model with Neuro‐Laguerre structure
- 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
- Hierarchical Newton and least squares iterative estimation algorithm for dynamic systems by transfer functions based on the impulse responses
- Hierarchical parameter and state estimation for bilinear systems
- Decomposition strategy-based hierarchical least mean square algorithm for control systems from the impulse responses
- Bayesian approach to identify Hammerstein–Wiener non‐linear model in presence of noise and disturbance
- The innovation algorithms for multivariable state‐space models
- 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
- Modeling and parameter identification of systems with multisegment piecewise-linear characteristics
- 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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