Nonparametric estimation of nonlinear dynamic systems using semirecursive regression estimates

DOI10.1016/J.NA.2009.02.128zbMath1238.93104OpenAlexW2090284295MaRDI QIDQ424379

Adam Krzyżak, Marian A. Partyka

Publication date: 31 May 2012

Published in: Nonlinear Analysis. Theory, Methods \& Applications. Series A: Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.na.2009.02.128

zbMATH Keywords

convergenceHammerstein systemnonparametric regression estimationsemirecursive estimates

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation and detection in stochastic control theory (93E10) Dynamical systems in control (37N35)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The identification of nonlinear biological systems: Wiener and Hammerstein Cascade models
• Nonparametric regression analysis of longitudinal data
• Recursive nonparametric identification of Hammerstein systems
• A distribution-free theory of nonparametric regression
• On estimation of a class of nonlinear systems by the kernel regression estimate
• Discrete time adaptive control of linear dynamic systems with a two-segment piecewise-linear asymmetric nonlinearity
• Almost everywhere convergence of a recursive regression function estimate and classification (Corresp.)
• Nonparametric System Identification
• On the design of nonlinear discrete-time predictors (Corresp.)
• Identification of discrete Hammerstein systems using kernel regression estimates
• Signal identification after noisy nonlinear transformations
• Non-linear system identification using the Hammerstein model
• Global convergence of the recursive kernel regression estimates with applications in classification and nonlinear system estimation
• An iterative method for the identification of nonlinear systems using a Uryson model
• On the L 1 convergence of kernel estimators of regression functions with applications in discrimination
• Identification of discrete Hammerstein systems by the Fourier series regression estimate
• The rates of convergence of kernel regression estimates and classification rules
• Hammerstein system identification by non-parametric regression estimation
• Recursive Estimates of Probability Densities
• A Note on Permanents

This page was built for publication: Nonparametric estimation of nonlinear dynamic systems using semirecursive regression estimates