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A New l0-LMS Algorithm With Adaptive Zero Attractor
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DOI：10.1109/LCOMM.2015.2490665.png)
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摘要
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In the l(0) norm constraint least mean square (l(0)-LMS) algorithm, the zero attractor is an important parameter which balances the trade-off between the convergence rate and steady-state error of the algorithm. However, there is no practically effective choice guideline of this parameter. In addition, the optimal value of this parameter should be time-varying when the measurement noise power varies with time, and a fixed value of the zero attractor is no longer suitable. In this letter, we propose an l(0)-LMS algorithm with adaptive zero attractor for applications with timevarying measurement noise signal, where the zero attractor is updated based on the criterion of maximizing the decrease of the transient mean square deviation.
Keyword:
l(0)-LMS algorithm
adaptive zero attractor
time-varying measurement noise signal
sparse system identification
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4.4
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1.3W
被引数:
2.2W
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