Recursive and iterative least squares parameter estimation algorithms for multiple-input-output-error systems with autoregressive noise
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Publication:2003303
DOI10.1007/s00034-017-0636-0zbMath1418.93279OpenAlexW2751604888MaRDI QIDQ2003303
Publication date: 16 July 2019
Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00034-017-0636-0
Multivariable systems, multidimensional control systems (93C35) Estimation and detection in stochastic control theory (93E10) Least squares and related methods for stochastic control systems (93E24)
Related Items (21)
A hierarchical least squares identification algorithm for Hammerstein nonlinear systems using the key term separation ⋮ Data filtering based maximum likelihood extended gradient method for multivariable systems with autoregressive moving average noise ⋮ Particle swarm optimization iterative identification algorithm and gradient iterative identification algorithm for Wiener systems with colored noise ⋮ Adaptive gradient-based iterative algorithm for multivariable controlled autoregressive moving average systems using the data filtering technique ⋮ Separable multi-innovation Newton iterative modeling algorithm for multi-frequency signals based on the sliding measurement window ⋮ The hierarchical iterative identification algorithm for multi-input-output-error systems with autoregressive noise ⋮ The data filtering based multiple‐stage Levenberg–Marquardt algorithm for Hammerstein nonlinear systems ⋮ 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 ⋮ The innovation algorithms for multivariable state‐space models ⋮ State space model identification of multirate processes with time-delay using the expectation maximization ⋮ Gradient-based iterative identification method for multivariate equation-error autoregressive moving average systems using the decomposition technique ⋮ Hierarchical Newton iterative parameter estimation of a class of input nonlinear systems based on the key term separation principle ⋮ Maximum likelihood recursive least squares estimation for multivariate equation-error ARMA systems ⋮ Auxiliary model based recursive generalized least squares identification algorithm for multivariate output-error autoregressive systems using the decomposition technique ⋮ On some parameter estimation algorithms for the nonlinear exponential autoregressive model ⋮ 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 ⋮ Hierarchical Newton and least squares iterative estimation algorithm for dynamic systems by transfer functions based on the impulse responses ⋮ Maximum likelihood-based recursive least-squares estimation for multivariable systems using the data filtering technique ⋮ Parameter estimation for a special class of nonlinear systems by using the over-parameterisation method and the linear filter ⋮ Recursive identification for multivariate autoregressive equation-error systems with autoregressive noise
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