Non-Parametric Nonlinear System Identification: An Asymptotic Minimum Mean Squared Error Estimator
From MaRDI portal
Publication:4978871
DOI10.1109/TAC.2010.2042343zbMath1368.93739OpenAlexW2164343167MaRDI QIDQ4978871
Publication date: 25 August 2017
Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1109/tac.2010.2042343
Linear regression; mixed models (62J05) Least squares and related methods for stochastic control systems (93E24) Identification in stochastic control theory (93E12)
Related Items
Variable selection in identification of a high dimensional nonlinear non-parametric system, Variable selection based on squared derivative averages, Structure discrimination in block-oriented models using linear approximations: a theoretic framework, Kernel-based identification of Wiener-Hammerstein system, Identification of Wiener, Hammerstein, and NARX systems as Markov chains with improved estimates for their nonlinearities, Local variable selection of nonlinear nonparametric systems by first order expansion, Weighted least squares based recursive parametric identification for the submodels of a PWARX system, Kernel based approaches to local nonlinear non-parametric variable selection, Variable selection of high-dimensional non-parametric nonlinear systems by derivative averaging to avoid the curse of dimensionality, Ranking the importance of variables in nonlinear system identification, System identification using kernel-based regularization: new insights on stability and consistency issues, Direct identification of the linear block in Wiener system, Kernel-based local order estimation of nonlinear nonparametric systems
