תקציר
This paper deals with robust estimation of AR parameters. We compare the performance of the LMS algorithm to the performance of two robust, adaptive algorithms: the LMAD algorithm of Shao and Nikias in which the error signal in the LMS algorithm is hard-limited before used to control the weights, and the LLMS algorithm in which the input process is soft-limited before the LMS algorithm is applied. The comparison is done in terms of rate of convergence and stability (steady state variance). We show that with a proper choice of limiting level, the LLMS algorithm outperforms the LMAD algorithms when applied to symmetric, α stable processes of 1 ≤ α ≤ 2.
שפה מקורית | אנגלית |
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עמודים | 230-233 |
מספר עמודים | 4 |
סטטוס פרסום | פורסם - 1996 |
פורסם באופן חיצוני | כן |
אירוע | Proceedings of the 1996 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP'96 - Corfu, Greece משך הזמן: 24 יוני 1996 → 26 יוני 1996 |
כנס
כנס | Proceedings of the 1996 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP'96 |
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עיר | Corfu, Greece |
תקופה | 24/06/96 → 26/06/96 |