Recursive least-squares algorithm for a characteristic model with coloured noise by means of the data filtering technique
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Publication:5028709
DOI10.1080/00207721.2021.1889707zbMath1483.93644OpenAlexW3134563835MaRDI QIDQ5028709
Publication date: 10 February 2022
Published in: International Journal of Systems Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207721.2021.1889707
Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10) Least squares and related methods for stochastic control systems (93E24)
Uses Software
Cites Work
- Unnamed Item
- A recursive least squares algorithm for pseudo-linear ARMA systems using the auxiliary model and the filtering technique
- System identification of nonlinear state-space models
- Data filtering based maximum likelihood gradient estimation algorithms for a multivariate equation-error system with ARMA noise
- Taylor polynomial solution of high-order nonlinear Volterra-Fredholm integro-differential equations
- Combined state and parameter estimation for a bilinear state space system with moving average noise
- State space model identification of multirate processes with time-delay using the expectation maximization
- Closed-loop estimation for randomly sampled measurements in target tracking system
- 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
- Synchronization of bidirectional \(N\)-coupled fractional-order chaotic systems with ring connection based on antisymmetric structure
- Piecewise reproducing kernel-based symmetric collocation approach for linear stationary singularly perturbed problems
- A new kernel functions based approach for solving 1-D interface 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
- Gradient estimation algorithms for the parameter identification of bilinear systems using the auxiliary model
- Iterative parameter estimation for signal models based on measured data
- 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
- Parametric identification with performance assessment of Wiener systems using brain storm optimization algorithm
- Weighted parameter estimation for Hammerstein nonlinear ARX systems
- Adaptive discrete-time sliding-mode control of nonlinear systems described by Wiener models
- Review of rational (total) nonlinear dynamic system modelling, identification, and control
- Non-linear system identification using the Hammerstein model
- Identification of the system comprising parallel Hammerstein branches
- Adaptive Distributed Estimation Based on Recursive Least-Squares and Partial Diffusion
- 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
- Combined estimation of the parameters and states for a multivariable state‐space system in presence of colored noise
- Separable multi‐innovation stochastic gradient estimation algorithm for the nonlinear dynamic responses of systems
- 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
- 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
- Maximum likelihood least squares‐based iterative methods for output‐error bilinear‐parameter models with colored noises
- Auxiliary model multiinnovation stochastic gradient parameter estimation methods for nonlinear sandwich systems