Statistical Properties of a Modified Welch Method That Uses Sample Percentiles

机译：使用样本百分比的改进韦尔奇方法的统计特性

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We present and analyze an alternative, more robust approach to the Welch’s overlapped segment averaging (WOSA) spectral estimator. Our method computes sample percentiles instead of averaging over multiple periodograms to estimate power spectral densities (PSDs). Bias and variance of the proposed estimator are derived for varying sample sizes and arbitrary percentiles. We have found excellent agreement between our expressions and data sampled from a white Gaussian noise process.

机译：我们在韦尔奇的重叠段平均（WOSA）光谱估计器上呈现并分析替代，更强大的方法。我们的方法计算样本百分比，而不是在多个时段下平均来估计功率谱密度（PSD）。推导出建议估计器的偏差和方差，用于不同的样本尺寸和任意百分位数。我们在我们的表情和数据中从白色高斯噪声过程中采样的数据之间找到了很好的一致性。

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《IEEE International Conference on Acoustics, Speech and Signal Processing》|2021年|5165-5169|共5页
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Felix Schwock; Shima Abadi;
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Gaussian noise; Conferences; Signal processing; Acoustics; Mathematical model; Speech processing;

机译：高斯噪音;会议;信号处理;声学;数学模型;语音处理;

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Statistical Properties of a Modified Welch Method That Uses Sample Percentiles

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