Data filtering based multi-innovation extended gradient method for controlled autoregressive autoregressive moving average systems using the maximum likelihood principle
From MaRDI portal
Publication:2228963
DOI10.1016/j.matcom.2016.06.006OpenAlexW2471333452MaRDI QIDQ2228963
Ahmed Alsaedi, Feiyan Chen, Feng Ding, Tasawar Hayat
Publication date: 19 February 2021
Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.matcom.2016.06.006
Related Items (7)
Modified multi-innovation stochastic gradient algorithm for Wiener-Hammerstein systems with backlash ⋮ Data filtering based maximum likelihood extended gradient method for multivariable systems with autoregressive moving average noise ⋮ Fitting the exponential autoregressive model through recursive search ⋮ The maximum likelihood least squares based iterative estimation algorithm for bilinear systems with autoregressive moving average noise ⋮ Maximum likelihood recursive least squares estimation for multivariate equation-error ARMA systems ⋮ Maximum likelihood-based recursive least-squares estimation for multivariable systems using the data filtering technique ⋮ Decomposition-based recursive least squares identification methods for multivariate pseudo-linear systems using the multi-innovation
Cites Work
- Unnamed Item
- Hierarchical parameter estimation for a class of MIMO Hammerstein systems based on the reframed models
- A proportional differential control method for a time-delay system using the Taylor expansion approximation
- Novel data filtering based parameter identification for multiple-input multiple-output systems using the auxiliary model
- Recursive least squares parameter estimation for a class of output nonlinear systems based on the model decomposition
- Robust \(\mathcal H_\infty\) filtering for nonlinear stochastic systems with uncertainties and Markov delays
- Maximum likelihood estimation and uniform inference with sporadic identification failure
- Bias compensation methods for stochastic systems with colored noise
- Unbiased identification of a class of multi-input single-output systems with correlated disturbances using bias compensation methods
- Parameter estimation for nonlinear dynamical adjustment models
- Accuracy analysis of time domain maximum likelihood method and sample maximum likelihood method for errors-in-variables and output error identification
- Maximum likelihood estimation of the fractional differencing parameter in an ARFIMA model using wavelets
- Improved least squares identification algorithm for multivariable Hammerstein systems
- Maximum likelihood based recursive parameter estimation for controlled autoregressive ARMA systems using the data filtering technique
- Parameter estimation for Hammerstein CARARMA systems based on the Newton iteration
- Semi-blind maximum-likelihood joint channel/data estimation for correlated channels in multiuser MIMO networks
- Modeling the dynamic sandwich system with hysteresis using NARMAX model
- Parameter estimation algorithms for multivariable Hammerstein CARMA systems
- The filtering based maximum likelihood recursive least squares estimation for multiple-input single-output systems
- Application of the Newton iteration algorithm to the parameter estimation for dynamical systems
- Minimum variance unbiased FIR filter for discrete time-variant systems
- Maximum likelihood stochastic gradient estimation for Hammerstein systems with colored noise based on the key term separation technique
- A novel APSO-aided maximum likelihood identification method for Hammerstein systems
- Estimation of parameters of the Makeham distribution using the least squares method
- Kalman filter-based identification for systems with randomly missing measurements in a network environment
- Blind Maximum-Likelihood Identification of Wiener Systems
- Maximum-Likelihood Estimation of the Discrete Coefficient of Determination in Stochastic Boolean Systems
- Fast Kalman-Like Optimal Unbiased FIR Filtering With Applications
This page was built for publication: Data filtering based multi-innovation extended gradient method for controlled autoregressive autoregressive moving average systems using the maximum likelihood principle
