Bias compensation‐based parameter estimation for output error moving average systems
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[1] Feng Ding,et al. Computers and Mathematics with Applications the Residual Based Extended Least Squares Identification Method for Dual-rate Systems , 2022 .
[2] Torbjörn Wigren,et al. Recursive prediction error identification and scaling of non-linear state space models using a restricted black box parameterization , 2006, Autom..
[3] J. Holst,et al. Convergence analysis of the RLS identification algorithm with exponential forgetting in stationary ARX‐structures , 1999 .
[4] Feng Ding,et al. Multi-innovation stochastic gradient algorithms for multi-input multi-output systems , 2009, Digit. Signal Process..
[5] Wei Xing Zheng,et al. On a least-squares-based algorithm for identification of stochastic linear systems , 1998, IEEE Trans. Signal Process..
[6] W. Zheng. Transfer function estimation from noisy input and output data , 1998 .
[7] Yong Zhang,et al. Bias compensation methods for stochastic systems with colored noise , 2011 .
[8] Y. Hui. Bias Compensation Recursive Least Squares Identification for Output Error Systems with Colored Noises , 2007 .
[9] Feng Ding,et al. Performance analysis of multi-innovation gradient type identification methods , 2007, Autom..
[10] Wei Xing Zheng,et al. A bias-correction method for indirect identification of closed-loop systems , 1995, Autom..
[11] Wei Xing Zheng,et al. A bias correction method for identification of linear dynamic errors-in-variables models , 2002, IEEE Trans. Autom. Control..
[12] Marion Gilson,et al. On the relation between a bias-eliminated least-squares (BELS) and an IV estimator in closed-loop identification , 2001, Autom..
[13] Torsten Söderström,et al. Extending the Frisch scheme for errors‐in‐variables identification to correlated output noise , 2008 .
[14] Wei Xing Zheng,et al. Convergence properties of bias‐eliminating algorithms for errors‐in‐variables identification , 2005 .
[15] Feng Ding,et al. A modified stochastic gradient based parameter estimation algorithm for dual-rate sampled-data systems , 2010, Digit. Signal Process..
[16] Yucai Zhu,et al. System identification using slow and irregular output samples , 2009 .
[17] F. Ding,et al. Least‐squares parameter estimation for systems with irregularly missing data , 2009 .
[18] Zhang Yong. Comparisons of bias compensation methods and other identification approaches for Box-Jenkins models , 2007 .
[19] Yanjun Liu,et al. Multi-innovation stochastic gradient algorithm for multiple-input single-output systems using the auxiliary model , 2009, Appl. Math. Comput..
[20] Feng Ding,et al. Bias compensation based recursive least-squares identification algorithm for MISO systems , 2006, IEEE Transactions on Circuits and Systems II: Express Briefs.
[21] Feng Ding,et al. Self-tuning control based on multi-innovation stochastic gradient parameter estimation , 2009, Syst. Control. Lett..
[22] Torsten Söderström,et al. Perspectives on errors-in-variables estimation for dynamic systems , 2002, Signal Process..
[23] Feng Ding,et al. Reconstruction of continuous-time systems from their non-uniformly sampled discrete-time systems , 2009, Autom..
[24] Kaushik Mahata,et al. An improved bias-compensation approach for errors-in-variables model identification , 2007, Autom..
[25] Feng Ding,et al. Several multi-innovation identification methods , 2010, Digit. Signal Process..