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利用谱相关函数的这些性质可以识别出噪声中的调制信号。
These characteristics of spectral correlation can be used to classify modulated signals, even when the signals are buried in noise.
一些不同的数字调制信号有着相同或相近的功率谱密度，但它们的谱相关函数却有明显区别。
Different types of digitally modulated signals that have similar, if not identical, power spectral density functions can have highly distinct spectral correlation functions.
该文根据自相关函数与谱密度函数之间的对应关系，提出了一种新的基于自相关函数的决策树归纳学习算法。
According to the relationship between auto correlation function and its spectral density, a new type of decision tree method based on signal analysis theory is proposed in this paper.
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