Modifier formula on mean square convergence of LMS algorithm
In describing the mean square convergence of the LMS algorithm, the update formula based on independence assumption will bring explicit errors, especially when step-size is large. In this paper, a modifier formula that describes the convergence well, is proposed. The simulations support the proposed...
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| Published in | Electronics letters Vol. 38; no. 19; p. 1 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Stevenage
John Wiley & Sons, Inc
12.09.2002
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0013-5194 1350-911X |
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| Abstract | In describing the mean square convergence of the LMS algorithm, the update formula based on independence assumption will bring explicit errors, especially when step-size is large. In this paper, a modifier formula that describes the convergence well, is proposed. The simulations support the proposed formula in different conditions. |
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| AbstractList | In describing the mean square convergence of the LMS algorithm, the update formula based on independence assumption will bring explicit errors, especially when step-size is large. In this paper, a modifier formula that describes the convergence well, is proposed. The simulations support the proposed formula in different conditions. |
| Author | Tang, Kun Du, Wen Gu, Yuantao Cui, Huijuan |
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| Copyright | Copyright The Institution of Engineering & Technology Sep 12, 2002 |
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| Snippet | In describing the mean square convergence of the LMS algorithm, the update formula based on independence assumption will bring explicit errors, especially when... |
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| SubjectTerms | Algorithms Computer simulation Convergence Errors Mean square values |
| Title | Modifier formula on mean square convergence of LMS algorithm |
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