引力波数据的小波熵滤波和互相关
Wavelet entropy filter and cross-correlation of gravitational wave data
摘要：
我们提出了一种方法，用于增强互相关的引力波信号最终存在于数据流中，否则不相关的噪声。该方法利用小波分解将互相关时间序列转换到时频空间。然后应用熵准则来识别最佳时频分辨率，即允许将信号集中在最小数量的小波系数中的分辨率。通过仅保持系数高于某个阈值，有可能重构其中公共信号的影响更强的互相关时间序列。我们测试了我们的方法对信号注入两个数据流的不相关的白噪声。
英文摘要：
We present a method for enhancing the cross-correlation of gravitational wave signals eventually present in data streams containing otherwise uncorrelated noise. Such method makes use of the wavelet decomposition to cast the cross-correlation time series in time-frequency space. Then an entropy criterion is applied to identify the best time frequency resolution, i.e. the resolution allowing to concentrate the signal in the smallest number of wavelet coefficients. By keeping only the coefficients above a certain threshold, it is possible to reconstruct a cross-correlation time series where the effect of common signal is stronger. We tested our method against signals injected over two data streams of uncorrelated white noise.
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