Iterative and recursive least squares estimation algorithms for moving average systems
Tài liệu tham khảo
Chouaba, 2012, A counter flow water to oil heat exchanger: MISO quasi linear parameter varying modeling and identification, Simulation Modelling Practice and Theory, 23, 87, 10.1016/j.simpat.2011.12.007
Ekonomou, 2012, Estimation of wind turbines optimal number and produced power in a wind farm using an artificial neural network model, Simulation Modelling Practice and Theory, 21, 21, 10.1016/j.simpat.2011.09.009
Saïd, 2011, High gain observer based on-line rotor and stator resistances estimation for IMs, Simulation Modelling Practice and Theory, 19, 1518, 10.1016/j.simpat.2011.03.006
Thanasis, 2011, Estimation of linear trend onset in time series, Simulation Modelling Practice and Theory, 19, 1384, 10.1016/j.simpat.2011.02.006
Ding, 2013, Hierarchical multi-innovation stochastic gradient algorithm for Hammerstein nonlinear system modeling, Applied Mathematical Modelling, 37, 1694, 10.1016/j.apm.2012.04.039
Desbouvries, 1996, On the identification of noisy MA models, IEEE Transactions on Automatic Control, 41, 1810, 10.1109/9.545746
Pappas, 2008, Modeling of the grounding resistance variation using ARMA models, Simulation Modelling Practice and Theory, 16, 560, 10.1016/j.simpat.2008.02.009
Franke, 1985, A Levinson–Durbin recursion for autoregressive-moving average processes, Biometrika, 72, 573, 10.1093/biomet/72.3.573
Tutunji, 2007, Mechatronic systems identification using an impulse response recursive algorithm, Simulation Modelling Practice and Theory, 15, 970, 10.1016/j.simpat.2007.05.004
Ding, 2005, Identification of Hammerstein nonlinear ARMAX systems, Automatica, 41, 10.1016/j.automatica.2005.03.026
Ding, 2011, Identification methods for Hammerstein nonlinear systems, Digital Signal Processing, 21, 215, 10.1016/j.dsp.2010.06.006
Wang, 2011, Least squares based and gradient based iterative identification for Wiener nonlinear systems, Signal Processing, 91, 1182, 10.1016/j.sigpro.2010.11.004
Ozmutlu, 2008, A Monte-Carlo simulation application for automatic new topic identification of search engine transaction logs, Simulation Modelling Practice and Theory, 16, 519, 10.1016/j.simpat.2008.02.005
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
Liu, 2010, Multi-innovation extended stochastic gradient algorithm and its performance analysis, Circuits Systems and Signal Processing, 29, 649, 10.1007/s00034-010-9174-8
Xie, 2010, Modeling and identification for non-uniformly periodically sampled-data systems, IET Control Theory and Applications, 4, 784, 10.1049/iet-cta.2009.0064
Ding, 2012, Performance analysis of the auxiliary model based least squares identification algorithm for one-step state delay systems, International Journal of Computer Mathematics, 89, 2019, 10.1080/00207160.2012.698008
Liu, 2009, Multi-innovation stochastic gradient algorithm for multiple-input single-output systems using the auxiliary model, Applied Mathematics and Computation, 215, 1477, 10.1016/j.amc.2009.07.012
Liu, 2010, Convergence of stochastic gradient estimation algorithm for multivariable ARX-like systems, Computers & Mathematics with Applications, 59, 2615, 10.1016/j.camwa.2010.01.030
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
Liu XG, 2010, Least squares based iterative identification for a class of multirate systems, Automatica, 46, 549, 10.1016/j.automatica.2010.01.007
Xiao, 2011, Parameter estimation for nonlinear dynamical adjustment models, Mathematical and Computer Modelling, 54, 1561, 10.1016/j.mcm.2011.04.027
Xiao, 2009, The residual based interactive least squares algorithms and simulation studies, Computers & Mathematics with Applications, 58, 1190, 10.1016/j.camwa.2009.02.037
Xiao, 2010, The residual based ESG algorithm and its performance analysis, Journal of the Franklin Institute-Engineering and Applied Mathematics, 347, 426, 10.1016/j.jfranklin.2009.05.008
Goodwin, 1984
F. Ding, Y. Shi, T. Chen,. Least squares identification of non-stationary MA systems, in: Proceedings of the 2005 American Control Conference (ACC2005), Portland, USA, June 8–10, 2005, pp. 4778–4783.
Ding, 2006, Performance analysis of estimation algorithms of non-stationary ARMA processes, IEEE Transactions on Signal Processing, 54, 1041, 10.1109/TSP.2005.862845
Wang, 2011, Least squares-based recursive and iterative estimation for output error moving average systems using data filtering, IET Control Theory and Applications, 5, 1648, 10.1049/iet-cta.2010.0416
Ljung, 1999
Ding, 2013
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
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
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
Wang, 2010, Gradient-based iterative parameter estimation for Box–Jenkins systems, Computers & Mathematics with Applications, 60, 1200, 10.1016/j.camwa.2010.06.001
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
Ding, 2012, Gradient based and least squares based iterative estimation algorithms for multi-input multi-output systems, Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering, 226, 43, 10.1177/0959651811409491
Ding, 2013, Two-stage least squares based iterative estimation algorithm for CARARMA system modeling, Applied Mathematical Modelling, 37, 4798, 10.1016/j.apm.2012.10.014