论文标题
过滤X对数递归的研究至少$ p $ - 功率算法
Study of filtered-x logarithmic recursive least $p$-power algorithm
论文作者
论文摘要
对于主动冲动噪声控制，提出了过滤的X递归最少$ p $ - 功率（FXRLP）算法，是通过最大程度地减少\ emph {a postteriori}错误的加权总和的加权总和。由于研究了目标噪声的特征，因此FXRLP算法实现了良好的性能和稳健性。为了获得更好的性能，我们开发了一个过滤的X对数递归最少$ p $ - 功率（FXLOGRLP）算法，该算法将$ p $ - 订购矩与对数订单时刻集成在一起。仿真结果表明，就收敛速率和降低降低而言，FXLOGRLP算法优于现有算法。
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.
