Recognition of Signals from Colored Noise Background in Generalized S‐Transform Domain
Recognition of Signals from Colored Noise Background in Generalized S‐Transform Domain
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DOI：
10.1002/cjg2.576
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发表时间：
2004-09
期刊：
影响因子：
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通讯作者：
Jinghuai Gao;Weishi Man;Shu-min Chen
中科院分区：
文献类型：
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作者：
Jinghuai Gao;Weishi Man;Shu-min Chen
研究了在S变换(ST)和广义S变换(GST)域中如何区分有色噪声信号。首先，推导了白噪声的平均ST和GST功率谱。结果表明，它们与频率呈线性关系。然后定性分析了有色噪声的局部GST功率谱。结果表明，色噪声的局域GST谱服从二自由度卡方分布。这些结论得到了蒙特卡罗模拟的验证。在此基础上，提出了一种有色噪声信号的识别方法，并用合成数据验证了该方法的有效性。
We study how to distinguish signals from colored noise in the S-transform (ST) and generalized S-transform (GST) domain. First, the mean ST and GST power spectra of white noise are derived. The result shows that they are related linearly with frequency. Then the local GST power spectrum of colored noise is qualitatively analyzed. It is concluded that the local GST spectrum of colored noise follows chi-square distribution with two degree of freedom. These conclusions are verified by Monte Carle simulation. Based on the above results, a method to distinguish signals from colored noise is proposed, and its effectiveness is proved by synthetic data.