Data filtering‐based parameter estimation algorithms for a class of nonlinear systems with colored noises
From MaRDI portal
Publication:6081010
DOI10.1002/oca.2985zbMath1522.93175OpenAlexW4322621225MaRDI QIDQ6081010
Unnamed Author, Unnamed Author, Chen Zhang, Unnamed Author
Publication date: 25 October 2023
Published in: Optimal Control Applications and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/oca.2985
Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10)
Cites Work
- Novel data filtering based parameter identification for multiple-input multiple-output systems using the auxiliary model
- Recursive least squares algorithm and gradient algorithm for Hammerstein-Wiener systems using the data filtering
- Hierarchical multi-innovation stochastic gradient algorithm for Hammerstein nonlinear system modeling
- New gradient based identification methods for multivariate pseudo-linear systems using the multi-innovation and the data filtering
- Convergence of the iterative algorithm for a general Hammerstein system identification
- Multi-innovation stochastic gradient algorithm for multiple-input single-output systems using the auxiliary model
- An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems
- A blind approach to the Hammerstein-Wiener model identification
- Modified multi-innovation stochastic gradient algorithm for Wiener-Hammerstein systems with backlash
- Parameter identification of a class of nonlinear systems based on the multi-innovation identification theory
- The filtering based parameter identification for bilinear-in-parameter systems
- Data filtering-based multi-innovation forgetting gradient algorithms for input nonlinear FIR-MA systems with piecewise-linear characteristics
- Model recovery for multi-input signal-output nonlinear systems based on the compressed sensing recovery theory
- Adaptive regularised kernel-based identification method for large-scale systems with unknown order
- Parameter estimation of Wiener systems based on the particle swarm iteration and gradient search principle
- A recursive parameter estimation algorithm for modeling signals with multi-frequencies
- Filtering-based multistage recursive identification algorithm for an input nonlinear output-error autoregressive system by using the key term separation technique
- Kalman filtering based gradient estimation algorithms for observer canonical state-space systems with moving average noises
- Particle filtering based parameter estimation for systems with output-error type model structures
- Parameter estimation for block‐oriented nonlinear systems using the key term separation
- Hierarchical parameter and state estimation for bilinear systems
- 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
- Multi‐innovation gradient parameter estimation for multivariable systems based on the maximum likelihood principle
- Accelerated identification algorithms for rational models based on the vector transformation
- Maximum likelihood least squares‐based iterative methods for output‐error bilinear‐parameter models with colored noises