Hammerstein system identification using nuclear norm minimization

DOI10.1016/J.AUTOMATICA.2012.06.013zbMath1258.93049OpenAlexW2161613854MaRDI QIDQ1937500

Younghee Han, Raymond A. de Callafon

Publication date: 1 March 2013

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2012.06.013

zbMATH Keywords

parameter estimationsingular value decompositionconvex optimization problemrank minimizationnuclear norm minimizationfinite impulse response (FIR)semidefinite programming problembilinear parametrizationblock-oriented system identificationfinite dimensional time dependencyHammerstein system identification

Mathematics Subject Classification ID

Semidefinite programming (90C22) System identification (93B30)

Related Items (6)

A nonparametric kernel-based approach to Hammerstein system identification ⋮ Identification of block-oriented nonlinear systems starting from linear approximations: a survey ⋮ 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 ⋮ Parameter estimation for nonlinear systems by using the data filtering and the multi-innovation identification theory ⋮ A nonlinear recursive instrumental variables identification method of Hammerstein ARMAX system

Uses Software

• SeDuMi
• YALMIP

Cites Work

• Unnamed Item
• Block-oriented nonlinear system identification
• Interior-Point Method for Nuclear Norm Approximation with Application to System Identification
• Using SeDuMi 1.02, A Matlab toolbox for optimization over symmetric cones
• Subspace identification of Hammerstein systems using least squares support vector machines

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