On estimation of a class of nonlinear systems by the kernel regression estimate

DOI10.1109/18.50380zbMath0714.62033OpenAlexW2162708512MaRDI QIDQ3200392

Adam Krzyżak

Publication date: 1990

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/18.50380

zbMATH Keywords

impulse responsekernel regression estimatedynamic linear subsystemnonlinear memoryless subsystemcorrelation methoddistribution-free pointwise and global convergenceestimation of multi-input single-output discrete Hammerstein systemestimation of the nonlinear memoryless subsystemnonlinearities of Lipschitz type

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Discrete-time control/observation systems (93C55) Estimation and detection in stochastic control theory (93E10)

Related Items (11)

Non-parametric identification of dynamic non-linear systems by a Hermite Series Approach ⋮ Identificaction of nonlinear block-oriented systems by the recursive kernel estimate ⋮ Recursive identification of continuous-time Hammerstein systems ⋮ Unnamed Item ⋮ Cascade non-linear system identification by a non-parametric method ⋮ Generalized Kernel Regression Estimate for the Identification of Hammerstein Systems ⋮ Nonparametric estimation of nonlinear dynamic systems using semirecursive regression estimates ⋮ Cascade systems de-noising and greedy calibrated approximation ⋮ Asymptotic local test for linearity in adaptive control ⋮ Global identification of nonlinear Hammerstein systems by recursive kernel approach ⋮ Testing linearity for NARX models

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