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Regular papers

Weighted hierarchical stochastic gradient identification algorithms for ARX models

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Pages 363-373 | Received 25 Jul 2019, Accepted 20 Sep 2020, Published online: 20 Oct 2020

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Tiancheng Zong, Junhong Li & Guoping Lu. (2023) Bias-compensated least squares and fuzzy PSO based hierarchical identification of errors-in-variables Wiener systems. International Journal of Systems Science 54:3, pages 633-651.
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Articles from other publishers (7)

Zhiwen Liu, Chongyang Han, Tianji Cheng, Enhai Liu & Ranjun Wang. (2024) Servo turntable adaptive step size momentum projection identification algorithm based on ARX model. Journal of the Franklin Institute 361:5, pages 106670.
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Zhiwen Liu, Tianji Cheng, Chongyang Han, Enhai Liu & Ranjun Wang. (2023) Momentum‐innovation recursive least squares identification algorithm for a servo turntable system based on the output error model. International Journal of Robust and Nonlinear Control 33:16, pages 10111-10135.
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Junhong Li, Hongrui Zhang, Juping Gu & Liang Hua. (2023) Parameter identification of fractional‐order Wiener system based on FF‐ESG and GI algorithms. Asian Journal of Control 25:6, pages 4512-4524.
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Yihan Guo & Cunbao Ma. (2022) Identification of time-delay Markov jumps autoregressive system with recursive expectation maximum and convex optimization algorithm. Transactions of the Institute of Measurement and Control 45:9, pages 1607-1618.
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Nanjiang Li, Yue Wang, Ziyun Wang & Yan Wang. (2022) Prediction of battery manufacturing capacity based on reinforcement learning network combination model. Prediction of battery manufacturing capacity based on reinforcement learning network combination model.
Tianyang Xu, Jing Chen, Yan Pu & Liuxiao Guo. (2021) Fractional-Based Stochastic Gradient Algorithms for Time-Delayed ARX Models. Circuits, Systems, and Signal Processing 41:4, pages 1895-1912.
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Donia Ben Halima Abid, Saif Eddine Abouda, Hanane Medhaffar & Mohamed Chtourou. (2021) An Improved Method for Stochastic Nonlinear System’s Identification Using Fuzzy-Type Output-Error Autoregressive Hammerstein–Wiener Model Based on Gradient Algorithm, Multi-Innovation, and Data Filtering Techniques. Complexity 2021, pages 1-29.
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