Skewness maximization for impulsive sources in blind deconvolution

P. Paajarvi, J. LeBlanc
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引用次数: 14

Abstract

In blind deconvolution problems, a deconvolution filter is often determined in an iterative manner, where the filter taps are adjusted to maximize some objective function of the filter output signal. The kurtosis of the filter output is a popular choice of objective function. In this paper, we investigate some advantages of using skewness, instead of kurtosis, in situations where the source signal is impulsive, i.e. has a sparse and asymmetric distribution. The comparison is based on the error surface characteristics of skewness and kurtosis.
盲反褶积中脉冲源偏度最大化
在盲反褶积问题中,反褶积滤波器通常以迭代方式确定,其中调整滤波器抽头以最大化滤波器输出信号的某个目标函数。滤波器输出的峰度是一种常用的目标函数选择。在本文中,我们研究了在源信号是脉冲的情况下,即具有稀疏和不对称分布的情况下,使用偏度而不是峰度的一些优点。比较是基于误差曲面的偏度和峰度特征。
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