滤波-x对数递归最小$p$ -幂算法的研究
Study of filtered-x logarithmic recursive least $p$-power algorithm
摘要：
针对脉冲噪声有源控制问题，通过最小化各\emph{a posteriori}误差的$p$-幂的加权和，提出了一种滤波-x递归最小$p$ -幂（FxRLP）算法.由于研究了目标噪声的特性，FxRLP算法具有良好的性能和鲁棒性。为了获得更好的性能，我们开发了一个过滤-x对数递归最小$p$ -功率（FxlogRLP）算法，它集成了$p$阶矩和阶矩。仿真结果表明，FxlogRLP算法在收敛速度和噪声抑制方面均优于现有算法。
英文摘要：
For active impulsive noise control, a filtered-x recursive least $p$-power (FxRLP) algorithm is proposed by minimizing the weighted summation of the $p$-power of the \emph{a posteriori} errors. Since the characteristic of the target noise is investigated, the FxRLP algorithm achieves good performance and robustness. To obtain a better performance, we develop a filtered-x logarithmic recursive least $p$-power (FxlogRLP) algorithm which integrates the $p$-order moment with the logarithmic-order moment. Simulation results demonstrate that the FxlogRLP algorithm is superior to the existing algorithms in terms of convergence rate and noise reduction.
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