Convergence of fixed-point iteration for the identification of Hammerstein and Wiener systems

DOI10.1002/rnc.2837zbMath1278.93282OpenAlexW1520916393MaRDI QIDQ2873470

Guoqi Li, Changyun Wen

Publication date: 24 January 2014

Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/rnc.2837

zbMATH Keywords

convergenceiterative algorithmfixed-point iterationHammerstein systemsnonlinear system identificationWiener systems

Mathematics Subject Classification ID

Identification in stochastic control theory (93E12) Applications of operator theory in optimization, convex analysis, mathematical programming, economics (47N10)

Related Items (3)

The modified extended Kalman filter based recursive estimation for Wiener nonlinear systems with process noise and measurement noise ⋮ Fixed point iteration in identifying bilinear models ⋮ System identification by operatorial cancellation of nonlinear terms and application to a class of Volterra models

Cites Work

• Convergence of normalized iterative identification of Hammerstein systems
• Parameter identification of Wiener systems with multisegment piecewise-linear nonlinearities
• Iterative identification of Hammerstein systems
• Adaptive tracking and recursive identification for Hammerstein systems
• The identification of nonlinear biological systems: LNL cascade models
• Identification of Hammerstein Systems with Quantized Observations
• Continuous-time Hammerstein system identification
• Identification of a Class of Nonlinear Autoregressive Models With Exogenous Inputs Based on Kernel Machines
• Identification of Wiener Systems With Clipped Observations
• Recursive identification of hammerstein systems with discontinuous nonlinearities containing dead-zones
• Pathwise Convergence of Recursive Identification Algorithms for Hammerstein Systems
• Convergence of the Iterative Hammerstein System Identification Algorithm

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