A State Evaluation Adaptive Differential Evolution Algorithm for FIR Filter Design
Due to conventional differential evolution algorithm is often trapped in local optima and premature convergence in high dimensional optimization problems, a State Evaluation Adaptive Differential Evolution algorithm (SEADE) is proposed in this paper. By using independent scale factor on each dimensi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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VSB-Technical University of Ostrava
2017-01-01
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| Series: | Advances in Electrical and Electronic Engineering |
| Subjects: | |
| Online Access: | http://advances.utc.sk/index.php/AEEE/article/view/2496 |
| _version_ | 1797827005885972480 |
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| author | Yong Wang Zhaosheng Teng Wen He Jianmin Li Radek Martinek |
| author_facet | Yong Wang Zhaosheng Teng Wen He Jianmin Li Radek Martinek |
| author_sort | Yong Wang |
| collection | DOAJ |
| description | Due to conventional differential evolution algorithm is often trapped in local optima and premature convergence in high dimensional optimization problems, a State Evaluation Adaptive Differential Evolution algorithm (SEADE) is proposed in this paper. By using independent scale factor on each dimension of optimization problem, and evaluating the distribution of population on each dimension, the SEADE correct the control parameters adaptively. External archive and a moving window evaluation mechanism on evolution state are introduced in SEADE to detect whether the evolution is stagnation or not, and with the help of opposition-based population, the algorithm can jump out of local optima basins. The results of experiments on several benchmarks show that the proposed algorithm is capable of improving the search performance of high dimensional optimization problems. And it is more efficient in design FIR digital filter using SEADE than conventional method like Parks-McClellan algorithm. |
| first_indexed | 2024-04-09T12:41:19Z |
| format | Article |
| id | doaj.art-e1de4c5a269649ab991c0e72f2a7d246 |
| institution | Directory Open Access Journal |
| issn | 1336-1376 1804-3119 |
| language | English |
| last_indexed | 2024-04-09T12:41:19Z |
| publishDate | 2017-01-01 |
| publisher | VSB-Technical University of Ostrava |
| record_format | Article |
| series | Advances in Electrical and Electronic Engineering |
| spelling | doaj.art-e1de4c5a269649ab991c0e72f2a7d2462023-05-14T20:50:12ZengVSB-Technical University of OstravaAdvances in Electrical and Electronic Engineering1336-13761804-31192017-01-0115577077910.15598/aeee.v15i5.2496952A State Evaluation Adaptive Differential Evolution Algorithm for FIR Filter DesignYong WangZhaosheng TengWen HeJianmin LiRadek MartinekDue to conventional differential evolution algorithm is often trapped in local optima and premature convergence in high dimensional optimization problems, a State Evaluation Adaptive Differential Evolution algorithm (SEADE) is proposed in this paper. By using independent scale factor on each dimension of optimization problem, and evaluating the distribution of population on each dimension, the SEADE correct the control parameters adaptively. External archive and a moving window evaluation mechanism on evolution state are introduced in SEADE to detect whether the evolution is stagnation or not, and with the help of opposition-based population, the algorithm can jump out of local optima basins. The results of experiments on several benchmarks show that the proposed algorithm is capable of improving the search performance of high dimensional optimization problems. And it is more efficient in design FIR digital filter using SEADE than conventional method like Parks-McClellan algorithm.http://advances.utc.sk/index.php/AEEE/article/view/2496differential evolution (de)external archivefir filteropposition-based populationstate evaluation. |
| spellingShingle | Yong Wang Zhaosheng Teng Wen He Jianmin Li Radek Martinek A State Evaluation Adaptive Differential Evolution Algorithm for FIR Filter Design Advances in Electrical and Electronic Engineering differential evolution (de) external archive fir filter opposition-based population state evaluation. |
| title | A State Evaluation Adaptive Differential Evolution Algorithm for FIR Filter Design |
| title_full | A State Evaluation Adaptive Differential Evolution Algorithm for FIR Filter Design |
| title_fullStr | A State Evaluation Adaptive Differential Evolution Algorithm for FIR Filter Design |
| title_full_unstemmed | A State Evaluation Adaptive Differential Evolution Algorithm for FIR Filter Design |
| title_short | A State Evaluation Adaptive Differential Evolution Algorithm for FIR Filter Design |
| title_sort | state evaluation adaptive differential evolution algorithm for fir filter design |
| topic | differential evolution (de) external archive fir filter opposition-based population state evaluation. |
| url | http://advances.utc.sk/index.php/AEEE/article/view/2496 |
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