Convergence of the auxiliary model-based multi-innovation generalized extended stochastic gradient algorithm for Box-Jenkins systems
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Publication:327476
DOI10.1007/s11071-015-2155-5zbMath1348.93086OpenAlexW636113288MaRDI QIDQ327476
Publication date: 19 October 2016
Published in: Nonlinear Dynamics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11071-015-2155-5
Related Items (11)
Multistage for identification of Wiener time delay systems based on hierarchical gradient approach ⋮ Recursive parameter estimation algorithms and convergence for a class of nonlinear systems with colored noise ⋮ A recursive least squares algorithm for pseudo-linear ARMA systems using the auxiliary model and the filtering technique ⋮ Auxiliary model based multi-innovation stochastic gradient identification algorithm for periodically non-uniformly sampled-data Hammerstein systems ⋮ The model equivalence based parameter estimation methods for Box-Jenkins systems ⋮ Recursive least squares algorithm for nonlinear dual-rate systems using missing-output estimation model ⋮ Active fault-tolerant linear parameter varying control for the pitch actuator of wind turbines ⋮ Robust hierarchical identification of Wiener systems in the presence of dynamic disturbances ⋮ Aitken based modified Kalman filtering stochastic gradient algorithm for dual-rate nonlinear models ⋮ A novel two-stage estimation algorithm for nonlinear Hammerstein-Wiener systems from noisy input and output data ⋮ A novel recursive learning identification scheme for Box-Jenkins model based on error data
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