Search Results - over-parameterization based recursive least squares method

Maximum Likelihood Recursive Generalized Extended Least Squares Estimation Methods for a Bilinear-parameter Systems with ARMA Noise Based on the Over-parameterization Model

Authors: Liu, Haibo Wang, Junwei Ji, Yan

Source: International Journal of Control, Automation and Systems ; volume 20, issue 8, page 2606-2615 ; ISSN 1598-6446 2005-4092

Availability: https://doi.org/10.1007/s12555-021-0367-7
https://link.springer.com/content/pdf/10.1007/s12555-021-0367-7.pdf
https://link.springer.com/article/10.1007/s12555-021-0367-7/fulltext.html

Decomposition based recursive least squares parameter estimation for input nonlinear equation-error systems

Authors: Fan Jiangbo Chen Huibo

Source: 2017 36th Chinese Control Conference (CCC). :2161-2165

Subject Terms: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/abstract/document/8027676/

A decomposition based recursive least squares identification algorithm for input nonlinear systems

Authors: Yongsong Xiao Huibo Chen

Source: 2016 Chinese Control and Decision Conference (CCDC). :5652-5656

Subject Terms: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: http://ieeexplore.ieee.org/document/7532009/
https://ieeexplore.ieee.org/abstract/document/7532009

Recursive subspace identification of Hammerstein models based on least squares support vector machines.

Authors: Bako, L. Mercére, G. Lecoeuche, S. et al.

Source: IET Control Theory & Applications (Institution of Engineering & Technology). Sep2009, Vol. 3 Issue 9, p1209-1216. 8p. 3 Graphs.

Subject Terms: *MATHEMATICAL models, *VECTOR analysis, *MACHINE theory, *ALGORITHMS, *INVARIANT subspaces

Decomposition-based least squares parameter estimation algorithm for input nonlinear systems using the key term separation technique

Authors: Yongsong Xiao Feng Ding Huibo Chen

Source: Nonlinear Dynamics. 79:2027-2035

Subject Terms: 0209 industrial biotechnology, 0103 physical sciences, 02 engineering and technology, 16. Peace & justice, 01 natural sciences

Access URL: https://link.springer.com/article/10.1007%2Fs11071-014-1791-5

High-Dimensional Imputation for the Social Sciences: A Comparison of State-of-The-Art Methods.

Authors: Costantini, Edoardo Lang, Kyle M. Reeskens, Tim et al.

Source: Sociological Methods & Research; May2025, Vol. 54 Issue 2, p448-499, 52p

Subject Terms: PRINCIPAL components analysis, MISSING data (Statistics), SOCIAL comparison, RANDOM forest algorithms, DATA analysis

Simulating Realistic Design Storms: A Joint Return Period Approach.

Authors: Cache, Tabea Bevacqua, Emanuele Zscheischler, Jakob et al.

Source: Water Resources Research; Jul2025, Vol. 61 Issue 7, p1-18, 18p

Subject Terms: FLOOD risk, RISK assessment, PRECIPITATION (Chemistry), FLOODS, RAINFALL simulators, COPULA functions

Geographic Terms: SWITZERLAND, ZURICH (Switzerland)

Highly efficient parameter estimation algorithms for Hammerstein non‐linear systems.

Authors: Mao, Yawen Ding, Feng Xu, Ling et al.

Source: IET Control Theory & Applications (Wiley-Blackwell); Mar2019, Vol. 13 Issue 4, p477-485, 9p

Auxiliary model‐based recursive least squares and stochastic gradient algorithms and convergence analysis for feedback nonlinear output‐error systems.

Authors: Miao, Guangqin Yang, Dan Ding, Feng

Source: International Journal of Adaptive Control & Signal Processing; Oct2024, Vol. 38 Issue 10, p3268-3289, 22p

Subject Terms: NONLINEAR systems, STOCHASTIC processes, LEAST squares, NONLINEAR estimation, NONLINEAR analysis, PARAMETER estimation

The filtering-based recursive least squares identification and convergence analysis for nonlinear feedback control systems with coloured noises.

Authors: Xu, Ling Xu, Huan Wei, Chun et al.

Source: International Journal of Systems Science; Dec2024, Vol. 55 Issue 16, p3461-3484, 24p

Subject Terms: FEEDBACK control systems, SYSTEM identification, STABILITY theory, MANUFACTURING processes, PARAMETER estimation, WHITE noise

Hierarchical recursive least squares parameter estimation methods for multiple‐input multiple‐output systems by using the auxiliary models.

Authors: Xing, Haoming Ding, Feng Pan, Feng et al.

Source: International Journal of Adaptive Control & Signal Processing; Nov2023, Vol. 37 Issue 11, p2983-3007, 25p

Subject Terms: PARAMETER estimation, MIMO systems

Auxiliary model‐based interval‐varying maximum likelihood estimation for nonlinear systems with missing data.

Authors: Xia, Huafeng Wu, Zhengle Xu, Sheng et al.

Source: International Journal of Robust & Nonlinear Control; 1/25/2024, Vol. 34 Issue 2, p1312-1323, 12p

Subject Terms: MISSING data (Statistics), NONLINEAR systems, NONLINEAR estimation

基于偏差补偿的双率 Hammerstein 输出误差系统辨识. (Chinese)

Alternate Title: Identification of Dual-rate Hammerstein Output Error Systems Based on Bias Compensation. (English)

Authors: 陆迅 曹余庆 谢莉

Source: Control Engineering of China; Jun2025, Vol. 32 Issue 6, p1092-1100, 9p

Parameter learning of multi‐input multi‐output Hammerstein system with measurement noises utilizing combined signals.

Authors: Li, Feng Sun, Xueqi Cao, Qingfeng

Source: International Journal of Adaptive Control & Signal Processing; Jul2025, Vol. 39 Issue 7, p1416-1433, 18p

Subject Terms: NOISE measurement, PARAMETER estimation, NONLINEAR systems, STATISTICAL correlation, MOVING average process, STATISTICAL smoothing, FUZZY neural networks

Input-output data filtering based recursive least squares identification algorithm for Hammerstein OEAR models.

Authors: Zhao, Junsheng Yu, Xingjiang Xia, Jianwei

Source: 2014 International Conference on Mechatronics & Control (ICMC); 2014, p2253-2258, 6p

Decomposition-based least squares parameter estimation algorithm for input nonlinear systems using the key term separation technique.

Authors: Chen, Huibo Ding, Feng Xiao, Yongsong

Source: Nonlinear Dynamics; Feb2015, Vol. 79 Issue 3, p2027-2035, 9p

Least squares based iterative identification algorithms for input nonlinear controlled autoregressive systems based on the auxiliary model.

Authors: Hu, Huiyi Ding, Rui

Source: Nonlinear Dynamics; Apr2014, Vol. 76 Issue 1, p777-784, 8p

Convergence Analysis of the Hierarchical Least Squares Algorithm for Bilinear-in-Parameter Systems.

Authors: Wang, Xuehai Ding, Feng Alsaadi, Fuad et al.

Source: Circuits, Systems & Signal Processing; Dec2016, Vol. 35 Issue 12, p4307-4330, 24p

Subject Terms: ALGORITHM software, PARAMETER estimation, COMPUTER simulation, STOCHASTIC convergence, MATHEMATICS theorems

Auxiliary Variable-Based Identification Algorithms for Uncertain-Input Models.

Authors: Chen, Jing Zhu, Quanmin Chandra, Budi et al.

Source: Circuits, Systems & Signal Processing; Jul2020, Vol. 39 Issue 7, p3389-3404, 16p

Subject Terms: ALGORITHMS, IDENTIFICATION, UNCERTAIN systems, LEAST squares

Data from: Separate block based parameter estimation method for Hammerstein systems

Authors: Zhang, Shuo Wang, Dongqing Liu, Feng

Subject Terms: Parameter estimation, Hammerstein systems, Separate block, least squares

Relation: Zhang S, Wang D, Liu F (2018) Separate block based parameter estimation method for Hammerstein systems. Royal Society Open Science 5(6): 172194.; http://hdl.handle.net/10255/dryad.181423

Availability: http://hdl.handle.net/10255/dryad.181423
https://doi.org/10.5061/dryad.k49ht50