稳定分布下的加权平均最小p-范数算法
doi: 10.3724/SP.J.1146.2005.00818
A Weighted Average Least p-Norm Algorithm under Alpha Stable Noise Conditions
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摘要: 该文提出一种新的适用于稳定分布噪声环境的自适应滤波算法，这种算法通过使加权平均误差函数的p-范数最小来实现自适应滤波。在这种算法的基础上，该文还得到两种新的动量LMP自适应算法。将这些新算法应用于估计AR模型的参数，计算机仿真的结果表明，该文提出的算法的性能比已有LMP算法的性能要更为优越。Abstract: This paper introduces a new adaptive filtering algorithm under the -stable noise conditions, which is obtained by minimizing the weighted average p-norm of error function. Two new versions of momentum LMP algorithm can be derived from the proposed one. Computer simulations on the channel equalization under the -stable noise conditions show that the proposed algorithms provide better estimation performance than those of the existing LMP algorithm.
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