Exhaustive Search and Power-Based Gradient Descent Algorithms for Time-Delayed FIR Models
In this study, two modified gradient descent (GD) algorithms are proposed for time-delayed models. To estimate the parameters and time-delay simultaneously, a redundant rule method is introduced, which turns the time-delayed model into an augmented model. Then, two GD algorithms can be used to ident...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/9244890 |
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| _version_ | 1832554766193917952 |
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| author | Hua Chen Yuejiang Ji |
| author_facet | Hua Chen Yuejiang Ji |
| author_sort | Hua Chen |
| collection | DOAJ |
| description | In this study, two modified gradient descent (GD) algorithms are proposed for time-delayed models. To estimate the parameters and time-delay simultaneously, a redundant rule method is introduced, which turns the time-delayed model into an augmented model. Then, two GD algorithms can be used to identify the time-delayed model. Compared with the traditional GD algorithms, these two modified GD algorithms have the following advantages: (1) avoid a high-order matrix eigenvalue calculation, thus, are more efficient for large-scale systems; (2) have faster convergence rates, therefore, are more practical in engineering practices. The convergence properties and simulation examples are presented to illustrate the efficiency of the two algorithms. |
| format | Article |
| id | doaj-art-c5b73af3d5d943ddbee014d1311935c1 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-c5b73af3d5d943ddbee014d1311935c12025-02-03T05:50:37ZengWileyComplexity1099-05262022-01-01202210.1155/2022/9244890Exhaustive Search and Power-Based Gradient Descent Algorithms for Time-Delayed FIR ModelsHua Chen0Yuejiang Ji1Wuxi Vocational College of Science and TechnologyWuxi Vocational College of Science and TechnologyIn this study, two modified gradient descent (GD) algorithms are proposed for time-delayed models. To estimate the parameters and time-delay simultaneously, a redundant rule method is introduced, which turns the time-delayed model into an augmented model. Then, two GD algorithms can be used to identify the time-delayed model. Compared with the traditional GD algorithms, these two modified GD algorithms have the following advantages: (1) avoid a high-order matrix eigenvalue calculation, thus, are more efficient for large-scale systems; (2) have faster convergence rates, therefore, are more practical in engineering practices. The convergence properties and simulation examples are presented to illustrate the efficiency of the two algorithms.http://dx.doi.org/10.1155/2022/9244890 |
| spellingShingle | Hua Chen Yuejiang Ji Exhaustive Search and Power-Based Gradient Descent Algorithms for Time-Delayed FIR Models Complexity |
| title | Exhaustive Search and Power-Based Gradient Descent Algorithms for Time-Delayed FIR Models |
| title_full | Exhaustive Search and Power-Based Gradient Descent Algorithms for Time-Delayed FIR Models |
| title_fullStr | Exhaustive Search and Power-Based Gradient Descent Algorithms for Time-Delayed FIR Models |
| title_full_unstemmed | Exhaustive Search and Power-Based Gradient Descent Algorithms for Time-Delayed FIR Models |
| title_short | Exhaustive Search and Power-Based Gradient Descent Algorithms for Time-Delayed FIR Models |
| title_sort | exhaustive search and power based gradient descent algorithms for time delayed fir models |
| url | http://dx.doi.org/10.1155/2022/9244890 |
| work_keys_str_mv | AT huachen exhaustivesearchandpowerbasedgradientdescentalgorithmsfortimedelayedfirmodels AT yuejiangji exhaustivesearchandpowerbasedgradientdescentalgorithmsfortimedelayedfirmodels |