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Evaluation of background noise for significance level identification

机译:评估背景噪声以识别重要性级别

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The paper deals with the identification of the significance level for testing the time-frequency transform of the data. The usual procedure of time-frequency significance testing is based on the knowledge of background spectrum. Very often, we have certain expectations about the character the background noise (White noise, Red noise, etc.). Our paper deals with the case when the character of the noise is unknown and may not be Gaussian despite our assumptions. Thus, we propose how to identify our own critical values for testing time-frequency transform significance with respect to the data character. We compare our findings with the critical quantile of χ.
机译:本文涉及识别显着性水平,以测试数据的时频变换。时频重要性测试的通常过程是基于背景光谱的知识。很多时候,我们对字符有一定的期望,即背景噪声(白噪声,红噪声等)。尽管假设,但本文处理的情况是噪声的特性未知,并且可能不是高斯噪声的情况。因此,我们提出了如何确定我们自己的临界值,以测试相对于数据特征的时频变换的重要性。我们将我们的发现与χ的临界分位数进行比较。

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