Convergence behavior analysis of FxLMS algorithms with different leaky term
In order to improve the robustness of conventional filtered-X LMS (FXLMS) algorithm, different leaky terms are introduced into the cost function. With different leaky term, the convergence behavior differs much. The detailed derivation of LASSO based FXLMS (L1-FXLMS) and elastic-net based FXLMS (L1/...
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| Main Authors: | , , |
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| 格式: | Conference or Workshop Item |
| 語言: | English |
| 出版: |
2023
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/169435 |
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| 總結: | In order to improve the robustness of conventional filtered-X LMS (FXLMS) algorithm, different leaky terms are introduced into the cost function. With different leaky term, the convergence behavior differs much. The detailed derivation of LASSO based FXLMS (L1-FXLMS) and elastic-net based FXLMS (L1/2-FXLMS) algorithms are presented. In addition, sufficient conditions for guaranteed convergence are derived for FxLMS algorithms with different leaky term. Furthermore, the convergence behavior of L1-FXLMS and L1/2-FXLMS algorithms are compared with conventional FXLMS and leaky FXLMS (L2-FXLMS) algorithms. It is indicated that L1-FXLMS could have faster convergence speed than L2-FXLMS with the premise of guaranteed convergence. Simulation and experiments are conducted to test the sufficient boundaries for guaranteed convergence of different FXLMS algorithms. |
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