Least squares based and gradient based iterative identification for Wiener nonlinear systems

Ding, 2005, Identification of Hammerstein nonlinear ARMAX systems, Automatica, 41, 1479, 10.1016/j.automatica.2005.03.026 Ding, 2007, Auxiliary model based least-squares identification methods for Hammerstein output-error systems, Systems & Control Letters, 56, 373, 10.1016/j.sysconle.2006.10.026 Umoh, 2010, An affine projection-based algorithm for identification of nonlinear Hammerstein systems, Signal Processing, 90, 2020, 10.1016/j.sigpro.2010.01.004 Wang, 2010, Auxiliary model-based RELS and MI-ELS algorithms for Hammerstein OEMA systems, Computers & Mathematics with Applications, 59, 3092, 10.1016/j.camwa.2010.02.030 Wang, 2010, Auxiliary model-based recursive generalized least squares parameter estimation for Hammerstein OEAR systems, Mathematical and Computer Modelling, 52, 309, 10.1016/j.mcm.2010.03.002 Vörös, 2003, Modeling and identification of Wiener systems with two-segment nonlinearities, IEEE Transactions on Control Systems Technology, 11, 253, 10.1109/TCST.2003.809238 Vörös, 2007, Parameter identification of Wiener systems with multisegment piecewise-linear nonlinearities, Systems & Control Letters, 56, 99, 10.1016/j.sysconle.2006.08.001 Aguirre, 2005, On the interpretation and practice of dynamical difference between Hammerstein and Wiener models, IEE Prooceedings of Control Theory and Applications, 152, 349, 10.1049/ip-cta:20045152 Hu, 2005, Strong consistence of recursive identification for Wiener systems, Automatica, 41, 1905, 10.1016/j.automatica.2005.06.006 Kozek, 2008, Identification of Wiener models using optimal local linear models, Simulation Modelling Practice and Theory, 16, 1055, 10.1016/j.simpat.2008.05.012 Figueroa, 2008, An approach for identification of uncertain Wiener systems, Mathematical and Computer Modelling, 48, 305, 10.1016/j.mcm.2007.09.012 Hagenblad, 2008, Maximum likelihood identification of Wiener models, Automatica, 44, 2697, 10.1016/j.automatica.2008.02.016 Ding, 2010, Gradient based and least-squares based iterative identification methods for OE and OEMA systems, Digital Signal Processing, 20, 664, 10.1016/j.dsp.2009.10.012 Liu, 2010, Least-squares based iterative algorithms for identifying Box-Jenkins models with finite measurement data, Digital Signal Processing, 20, 1458, 10.1016/j.dsp.2010.01.004 Wang, 2010, Gradient-based iterative parameter estimation for Box-Jenkins systems, Computers & Mathematics with Applications, 60, 1200, 10.1016/j.camwa.2010.06.001 Kapetanios, 2003, A note on an iterative least-squares estimation method for ARMA and VARMA models, Economics Letters, 79, 305, 10.1016/S0165-1765(03)00005-3 Bai, 2006, Least squares solutions of bilinear equations, Systems & Control Letters, 55, 466, 10.1016/j.sysconle.2005.09.010 Ding, 2005, Hierarchical gradient-based identification of multivariable discrete-time systems, Automatica, 41, 315, 10.1016/j.automatica.2004.10.010 Ding, 2005, Hierarchical least squares identification methods for multivariable systems, IEEE Transactions on Automatic Control, 50, 397, 10.1109/TAC.2005.843856 Ding, 2005, Hierarchical identification of lifted state-space models for general dual-rate systems, IEEE Transactions on Circuits and Systems—I: Regular Papers, 52, 1179, 10.1109/TCSI.2005.849144 D.Q. Wang, Y.Y. Chu, F. Ding, Identification methods for Wiener nonlinear systems based on the least squares and gradient iterations, in: 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, December 16–18, 2009, Shanghai, China, pp. 3632–3636. Ding, 2007, Performance analysis of multi-innovation gradient type identification methods, Automatica, 43, 1, 10.1016/j.automatica.2006.07.024 Ding, 2010, Several multi-innovation identification methods, Digital Signal Processing, 20, 1027, 10.1016/j.dsp.2009.10.030 Wang, 2010, Performance analysis of the auxiliary models based multi-innovation stochastic gradient estimation algorithm for output error systems, Digital Signal Processing, 20, 750, 10.1016/j.dsp.2009.09.002 Ding, 2009, Auxiliary model based multi-innovation extended stochastic gradient parameter estimation with colored measurement noises, Signal Processing, 89, 1883, 10.1016/j.sigpro.2009.03.020 Han, 2009, Multi-innovation stochastic gradient algorithms for multi-input multi-output systems, Digital Signal Processing, 19, 545, 10.1016/j.dsp.2008.12.002 Zhang, 2009, Self-tuning control based on multi-innovation stochastic gradient parameter estimation, Systems & Control Letters, 58, 69, 10.1016/j.sysconle.2008.08.005 Ding, 2010, Multi-innovation least squares identification for linear and pseudo-linear regression models, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 40, 767, 10.1109/TSMCB.2009.2028871 Xie, 2010, Modeling and identification for non-uniformly periodically sampled-data systems, IET Control Theory & Applications, 4, 784, 10.1049/iet-cta.2009.0064 Bai, 1998, An optimal two-stage identification algorithm for Hammerstein–Wiener nonlinear systems, Automatica, 34, 333, 10.1016/S0005-1098(97)00198-2 Wang, 2008, Extended stochastic gradient identification algorithms for Hammerstein–Wiener ARMXA Systems, Computers and Mathematics with Applications, 56, 3157, 10.1016/j.camwa.2008.07.015 Liu, 2007, Iterative identification of Hammerstein systems, Automatica, 43, 346, 10.1016/j.automatica.2006.09.004 Cerone, 2003, Parameter bounds for discrete-time Hammerstein models with bounded output errors, IEEE Transactions on Automatic Control, 48, 1855, 10.1109/TAC.2003.817945 Ding, 2010, Least squares parameter estimation with irregularly missing data, International Journal of Adaptive Control and Signal Processing, 24, 540 Ding, 2009, Reconstruction of continuous-time systems from their non-uniformly sampled discrete-time systems, Automatica, 45, 324, 10.1016/j.automatica.2008.08.007 Ding, 2010, Partially coupled stochastic gradient identification methods for non-uniformly sampled systems, IEEE Transaction on Automatic Control, 55, 1976, 10.1109/TAC.2010.2050713 Liu, 2009, An auxiliary model based recursive least squares parameter estimation algorithm for non-uniformly sampled multirate systems, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 223, 445 Ding, 2008, Parameter identification and intersample output estimation for dual-rate systems, IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 38, 966, 10.1109/TSMCA.2008.923030 Ding, 2010, A modified stochastic gradient based parameter estimation algorithm for dual-rate sampled-data systems, Digital Signal Processing, 20, 1238, 10.1016/j.dsp.2009.10.023 Wang, 2010, Input–output data filtering based recursive least squares identification for CARARMA systems, Digital Signal Processing, 20, 991, 10.1016/j.dsp.2009.12.006 F. Ding, P.X. Liu, G. Liu, Identification methods for Hammerstein nonlinear systems, Digital Signal Processing 21 (2) (2011), doi:10.1016/j.dsp.2010.06.006