Convergence of normalized iterative identification of Hammerstein systems

DOI10.1016/j.sysconle.2011.07.010zbMath1229.93038OpenAlexW2013244010MaRDI QIDQ647646

Changyun Wen, Guoqi Li

Publication date: 24 November 2011

Published in: Systems \& Control Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sysconle.2011.07.010

zbMATH Keywords

convergenceparameter estimationHammerstein systemsnormalized iterative identification

Mathematics Subject Classification ID

System identification (93B30) Control/observation systems governed by functional relations other than differential equations (such as hybrid and switching systems) (93C30)

Related Items (9)

Improved least squares identification algorithm for multivariable Hammerstein systems ⋮ Filtering‐based multi‐innovation recursive identification methods for input nonlinear systems with piecewise‐linear nonlinearity based on the optimization criterion ⋮ A novel APSO-aided weighted LSSVM method for nonlinear Hammerstein system identification ⋮ Fixed point iteration in identifying bilinear models ⋮ Recursive identification of time-varying systems: self-tuning and matrix RLS algorithms ⋮ Iterative identification of block-oriented nonlinear systems based on biconvex optimization ⋮ A nonlinear recursive instrumental variables identification method of Hammerstein ARMAX system ⋮ Correlation analysis-based error compensation recursive least-square identification method for the Hammerstein model ⋮ Convergence of fixed-point iteration for the identification of Hammerstein and Wiener systems

Cites Work

• Iterative identification of Hammerstein systems
• Adaptive tracking and recursive identification for Hammerstein systems
• An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems
• Identification of Hammerstein Systems with Quantized Observations
• Nonparametric System Identification
• Identification of a Class of Nonlinear Autoregressive Models With Exogenous Inputs Based on Kernel Machines
• Recursive identification of hammerstein systems with discontinuous nonlinearities containing dead-zones
• Combined Parametric–Nonparametric Identification of Hammerstein Systems
• Pathwise Convergence of Recursive Identification Algorithms for Hammerstein Systems
• Convergence of the Iterative Hammerstein System Identification Algorithm
• Hammerstein system identification by non-parametric instrumental variables

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