Least squares based and gradient based iterative identification for Wiener nonlinear systems
Top Cited Papers
- 21 November 2010
- journal article
- Published by Elsevier BV in Signal Processing
- Vol. 91 (5), 1182-1189
- https://doi.org/10.1016/j.sigpro.2010.11.004
Abstract
No abstract availableKeywords
This publication has 40 references indexed in Scilit:
- Auxiliary model based recursive generalized least squares parameter estimation for Hammerstein OEAR systemsMathematical and Computer Modelling, 2010
- An affine projection-based algorithm for identification of nonlinear Hammerstein systemsSignal Processing, 2010
- Auxiliary model-based RELS and MI-ELS algorithm for Hammerstein OEMA systemsComputers & Mathematics with Applications, 2010
- Identification of Wiener models using optimal local linear modelsSimulation Modelling Practice and Theory, 2008
- Auxiliary model-based least-squares identification methods for Hammerstein output-error systemsSystems & Control Letters, 2007
- Parameter identification of Wiener systems with multisegment piecewise-linear nonlinearitiesSystems & Control Letters, 2007
- Strong consistence of recursive identification for Wiener systemsAutomatica, 2005
- Identification of Hammerstein nonlinear ARMAX systemsAutomatica, 2005
- On the interpretation and practice of dynamical differences between Hammerstein and Wiener modelsIEE Proceedings - Control Theory and Applications, 2005
- Modeling and identification of wiener systems with two-segment nonlinearitiesIEEE Transactions on Control Systems Technology, 2003