Suchergebnisse - multiinnovation stochastic gradient algorithm

Correlation Analysis-based Stochastic Gradient and Least Squares Identification Methods for Errors-in-variables Systems Using the Multiinnovation

Autoren: Shujun Fan Tasawar Hayat Ahmed Alsaedi et al.

Quelle: International Journal of Control, Automation and Systems. 19:289-300

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

Zugangs-URL: https://link.springer.com/article/10.1007/s12555-019-0970-z
https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002676376

Correlation Analysis-based Stochastic Gradient and Least Squares Identification Methods for Errors-in-variables Systems Using the Multiinnovation.

Autoren: Fan, Shujun Xu, Ling Ding, Feng et al.

Quelle: International Journal of Control, Automation & Systems; 2021, Vol. 19 Issue 1, p289-300, 12p

Multierror stochastic gradient algorithm for identification of a Hammerstein system with random noise and its application in the modeling of a continuous stirring tank reactor.

Autoren: Jing, Shaoxue

Quelle: Optimal Control - Applications & Methods; May2023, Vol. 44 Issue 3, p1510-1522, 13p

Schlagwörter: SYSTEM identification, UNCERTAINTY (Information theory), PROBABILITY density function, ALGORITHMS, MANUFACTURING processes

Auxiliary model multiinnovation stochastic gradient parameter estimation methods for nonlinear sandwich systems.

Autoren: Xu, Ling Ding, Feng Yang, Erfu

Quelle: International Journal of Robust & Nonlinear Control; 1/10/2021, Vol. 31 Issue 1, p148-165, 18p

Schlagwörter: NONLINEAR systems, PARAMETER estimation, STOCHASTIC models, NONLINEAR estimation, NONLINEAR equations, NONLINEAR oscillators

Maximum likelihood‐based gradient estimation for multivariable nonlinear systems using the multiinnovation identification theory.

Autoren: Xia, Huafeng Ji, Yan Xu, Ling et al.

Quelle: International Journal of Robust & Nonlinear Control; 9/25/2020, Vol. 30 Issue 14, p5446-5463, 18p

Schlagwörter: NONLINEAR estimation, NONLINEAR systems, PARAMETER estimation, IDENTIFICATION, PARAMETER identification, ALGORITHMS, COMPUTATIONAL complexity, MULTIVARIABLE testing

Model transformation based distributed stochastic gradient algorithm for multivariate output-error systems.

Autoren: Liu, Qinyao Chen, Feiyan

Quelle: International Journal of Systems Science; May2023, Vol. 54 Issue 7, p1484-1502, 19p

Schlagwörter: ALGORITHMS, PARAMETER estimation, COMPUTATIONAL complexity, INFORMATION sharing, DISTRIBUTED algorithms

反馈非线性系统随机梯度辨识算法及其收敛性. (Chinese)

Alternate Title: Stochastic gradient identification algorithm and its convergence for feedback nonlinear systems. (English)

Autoren: 魏 纯 徐 玲 丁 锋

Quelle: Control Theory & Applications / Kongzhi Lilun Yu Yinyong; Oct2023, Vol. 40 Issue 10, p1757-1764, 8p

Schlagwörter: NONLINEAR systems

Overall recursive least squares and overall stochastic gradient algorithms and their convergence for feedback nonlinear controlled autoregressive systems.

Autoren: Wei, Chun Zhang, Xiao Xu, Ling et al.

Quelle: International Journal of Robust & Nonlinear Control; Jun2022, Vol. 32 Issue 9, p5534-5554, 21p

Schlagwörter: NONLINEAR systems, PARAMETER estimation, STOCHASTIC processes, ALGORITHMS, NONLINEAR estimation

Maximum likelihood extended gradient‐based estimation algorithms for the input nonlinear controlled autoregressive moving average system with variable‐gain nonlinearity.

Autoren: Liu, Ximei Fan, Yamin

Quelle: International Journal of Robust & Nonlinear Control; Jun2021, Vol. 31 Issue 9, p4017-4036, 20p

Schlagwörter: MOVING average process, EXPECTATION-maximization algorithms, PARAMETER estimation, PARAMETER identification, SYSTEM identification, ALGORITHMS

Maximum likelihood‐based gradient estimation for multivariable nonlinear systems using the multiinnovation identification theory

Autoren: Huafeng Xia Yan Ji Ling Xu et al.

Quelle: International Journal of Robust and Nonlinear Control. 30:5446-5463

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

Zugangs-URL: https://onlinelibrary.wiley.com/doi/10.1002/rnc.5086

Bias compensated stochastic gradient algorithm for identification of an ARX‐type nonlinear rational model and its application in modeling of the dynamic of the cellular toxicity.

Autoren: Jing, Shaoxue Kiely, Janice Luxton, Richard

Quelle: International Journal of Robust & Nonlinear Control; Jun2022, Vol. 32 Issue 9, p5268-5280, 13p

Schlagwörter: PARAMETER identification, DYNAMIC models, ALGORITHMS, AMMONIUM chloride, INFORMATION modeling

Auxiliary model maximum likelihood gradient‐based iterative identification for feedback nonlinear systems.

Autoren: Liu, Lijuan Li, Fu Ma, Junxia et al.

Quelle: Optimal Control - Applications & Methods; Sep2024, Vol. 45 Issue 5, p2346-2363, 18p

Schlagwörter: NONLINEAR systems, MOVING average process, COMPUTER simulation, ALGORITHMS, NOISE

Hierarchical maximum likelihood generalized extended stochastic gradient algorithms for bilinear‐in‐parameter systems.

Autoren: Liu, Haibo Wang, Junwei Meng, Xiangxiang

Quelle: Optimal Control - Applications & Methods; Mar2022, Vol. 43 Issue 2, p402-417, 16p

Schlagwörter: PARAMETER estimation, AUTOREGRESSIVE models, MOVING average process, ALGORITHMS, NONLINEAR systems

Maximum Likelihood Multi-innovation Stochastic Gradient Estimation for Multivariate Equation-error Systems.

Autoren: Liu, Lijuan Ding, Feng Wang, Cheng et al.

Quelle: International Journal of Control, Automation & Systems; Oct2018, Vol. 16 Issue 5, p2528-2537, 10p

Hierarchical extended parameter identification methods and convergence for finite impulse response moving average models based on the hierarchical identification principle.

Autoren: Ding, Feng Xu, Ling Zhang, Xiao et al.

Quelle: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems & Control Engineering; Nov2025, Vol. 239 Issue 10, p1719-1746, 28p

Parameter identification of a nonlinear radial basis function‐based state‐dependent autoregressive network with autoregressive noise via the filtering technique and the multiinnovation theory.

Autoren: Zhou, Yihong Ma, Fengying Ding, Feng et al.

Quelle: International Journal of Robust & Nonlinear Control; 11/25/2020, Vol. 30 Issue 17, p7619-7634, 16p

Schlagwörter: PARAMETER estimation, PARAMETER identification, AUTOREGRESSIVE models, RADIAL basis functions, ALGORITHMS, NOISE

Maximum likelihood extended gradient‐based estimation algorithms for the input nonlinear controlled autoregressive moving average system with variable‐gain nonlinearity

Autoren: Ximei Liu Yamin Fan

Quelle: International Journal of Robust and Nonlinear Control. 31:4017-4036

Schlagwörter: 0209 industrial biotechnology, 02 engineering and technology

Zugangs-URL: https://onlinelibrary.wiley.com/doi/10.1002/rnc.5450

Weighted hierarchical stochastic gradient identification algorithms for ARX models.

Autoren: Dong, Rui-Qi Zhang, Ying Wu, Ai-Guo

Quelle: International Journal of Systems Science; Jan2021, Vol. 52 Issue 2, p363-373, 11p

Schlagwörter: ALGORITHMS, PARAMETER identification, IDENTIFICATION, SYSTEM identification, HIERARCHICAL Bayes model

Decomposition‐based over‐parameterization forgetting factor stochastic gradient algorithm for Hammerstein‐Wiener nonlinear systems with non‐uniform sampling.

Autoren: Liu, Qilin Xiao, Yongsong Ding, Feng et al.

Quelle: International Journal of Robust & Nonlinear Control; Aug2021, Vol. 31 Issue 12, p6007-6024, 18p

Schlagwörter: NONLINEAR systems, ALGORITHMS, RECOLLECTION (Psychology), PARAMETERIZATION, NONLINEAR equations, PARAMETER estimation

Identification of Wiener systems based on the variable forgetting factor multierror stochastic gradient and the key term separation.

Autoren: Jing, Shaoxue Pan, Tianhong Zhu, Quanmin

Quelle: International Journal of Adaptive Control & Signal Processing; Dec2021, Vol. 35 Issue 12, p2537-2549, 13p

Schlagwörter: SYSTEM identification, PROBABILITY density function, ALGORITHMS, ERROR functions, RECOLLECTION (Psychology)