Study of a new fast adaptive filtering algorithm
A new fast adaptive filtering algorithm was presented by using the correlations between the signal’s former and latter sampling times. The proof of the new algorithm was also presented, which showed that its optimal weight vector was the solution of generalized Wiener equation. The new algorithm was...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2005-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/74666066/ |
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| _version_ | 1841537256418967552 |
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| author | WANG Zhen-li ZHANG Xiong-wei YANG Ji-bin CHEN Gong |
| author_facet | WANG Zhen-li ZHANG Xiong-wei YANG Ji-bin CHEN Gong |
| author_sort | WANG Zhen-li |
| collection | DOAJ |
| description | A new fast adaptive filtering algorithm was presented by using the correlations between the signal’s former and latter sampling times. The proof of the new algorithm was also presented, which showed that its optimal weight vector was the solution of generalized Wiener equation. The new algorithm was of simple structure, fast convergence, less stable maladjustment. It had the ability of dealing with many signals, including noncorrelation signal and strong correlation signal. However, its computational complexity was comparable to that of NLMS algorithm. Simulation results show that for noncorrelation signal, the stable maladjustment of the proposed algorithm is less than that of VS-NLMS algorithm, and its convergence is comparable to that of the algorithm proposed in reference but faster than that of L.E-LMS algorithm. For high correlation signal, its performance is superior to those of NLMS algorithm and DCR-LMS algorithm. |
| format | Article |
| id | doaj-art-25db8abe1c3a4404bee1fec07c2f138d |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2005-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-25db8abe1c3a4404bee1fec07c2f138d2025-01-14T08:40:51ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2005-01-0174666066Study of a new fast adaptive filtering algorithmWANG Zhen-liZHANG Xiong-weiYANG Ji-binCHEN GongA new fast adaptive filtering algorithm was presented by using the correlations between the signal’s former and latter sampling times. The proof of the new algorithm was also presented, which showed that its optimal weight vector was the solution of generalized Wiener equation. The new algorithm was of simple structure, fast convergence, less stable maladjustment. It had the ability of dealing with many signals, including noncorrelation signal and strong correlation signal. However, its computational complexity was comparable to that of NLMS algorithm. Simulation results show that for noncorrelation signal, the stable maladjustment of the proposed algorithm is less than that of VS-NLMS algorithm, and its convergence is comparable to that of the algorithm proposed in reference but faster than that of L.E-LMS algorithm. For high correlation signal, its performance is superior to those of NLMS algorithm and DCR-LMS algorithm.http://www.joconline.com.cn/zh/article/74666066/adaptive filterNLMS algorithmWiener equationcorrelation |
| spellingShingle | WANG Zhen-li ZHANG Xiong-wei YANG Ji-bin CHEN Gong Study of a new fast adaptive filtering algorithm Tongxin xuebao adaptive filter NLMS algorithm Wiener equation correlation |
| title | Study of a new fast adaptive filtering algorithm |
| title_full | Study of a new fast adaptive filtering algorithm |
| title_fullStr | Study of a new fast adaptive filtering algorithm |
| title_full_unstemmed | Study of a new fast adaptive filtering algorithm |
| title_short | Study of a new fast adaptive filtering algorithm |
| title_sort | study of a new fast adaptive filtering algorithm |
| topic | adaptive filter NLMS algorithm Wiener equation correlation |
| url | http://www.joconline.com.cn/zh/article/74666066/ |
| work_keys_str_mv | AT wangzhenli studyofanewfastadaptivefilteringalgorithm AT zhangxiongwei studyofanewfastadaptivefilteringalgorithm AT yangjibin studyofanewfastadaptivefilteringalgorithm AT chengong studyofanewfastadaptivefilteringalgorithm |