Wavelet Based Outlier Correction for Power Controlled Turning Point Detecti...

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英文文献：Wavelet Based Outlier Correction for Power Controlled Turning Point Detection in Surveillance Systems-基于小波的监视系统中电源控制的转折点检测的离群点校正
英文文献作者：Yushu Li
英文文献摘要：
Detection turning points in unimodel has various applications to time series which have cyclic periods. Related techniques are widely explored in the field of statistical surveillance, that is, on-line turning point detection procedures. This paper will first present a power controlled turning point detection method based on the theory of the likelihood ratio test in statistical surveillance. Next we show how outliers will influence the performance of this methodology. Due to the sensitivity of the surveillance system to outliers, we finally present a wavelet multiresolution (MRA) based outlier elimination approach, which can be combined with the on-line turning point detection process and will then alleviate the false alarm problem introduced by the outliers.

uniimodel的检测转折点对具有周期的时间序列有多种应用。相关技术在统计监测领域得到了广泛的探索，即在线转折点检测程序。本文首先提出了一种基于似然比检验理论的功率控制拐点检测方法。接下来，我们将展示异常值将如何影响此方法的性能。由于监测系统对异常值的敏感性，我们最后提出了一种基于小波多分辨率的异常值消除方法，该方法可以与在线转折点检测过程相结合，从而缓解异常值带来的误报问题。

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