Parameter Identification of ARX Models Based on Modified Momentum Gradient Descent Algorithm
Joint Authors
Tu, Quan
Rong, Yingjiao
Chen, Jing
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-17
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The parameter estimation problem of the ARX model is studied in this paper.
First, some traditional identification algorithms are briefly introduced, and then a new parameter estimation algorithm—the modified momentum gradient descent algorithm—is developed.
Two gradient directions with their corresponding step sizes are derived in each iteration.
Compared with the traditional parameter identification algorithms, the modified momentum gradient descent algorithm has a faster convergence rate.
A simulation example shows that the proposed algorithm is effective.
American Psychological Association (APA)
Tu, Quan& Rong, Yingjiao& Chen, Jing. 2020. Parameter Identification of ARX Models Based on Modified Momentum Gradient Descent Algorithm. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1145631
Modern Language Association (MLA)
Tu, Quan…[et al.]. Parameter Identification of ARX Models Based on Modified Momentum Gradient Descent Algorithm. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1145631
American Medical Association (AMA)
Tu, Quan& Rong, Yingjiao& Chen, Jing. Parameter Identification of ARX Models Based on Modified Momentum Gradient Descent Algorithm. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1145631
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1145631