文件名称:non-Gaussian-noise-Identification
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该文提出一种基于广义分数阶傅里叶变换和分数低阶Wigner-Ville 分布的数字调制识别新方法，该方法提取广义分数阶傅里叶变换的零
中心归一化瞬时幅度谱密度的最大值和分数低阶Wigner-Ville 分布幅度的最大值作为识别特征参数，并采用判决树分类器，实现了非高斯噪声下数字调制信号识别。-This paper presents a generalized fractional Fourier transform and fractional lower order Wigner-Ville distribution of new digital modulation recognition method, the method to extract generalized fractional Fourier transform, the center is one of the instantaneous amplitude spectral density The maximum amplitude values and fractional lower order Wigner-Ville distribution as an identifying characteristic parameters, and decision tree classifier, to achieve a non-Gaussian noise under digital modulation signal recognition.
中心归一化瞬时幅度谱密度的最大值和分数低阶Wigner-Ville 分布幅度的最大值作为识别特征参数，并采用判决树分类器，实现了非高斯噪声下数字调制信号识别。-This paper presents a generalized fractional Fourier transform and fractional lower order Wigner-Ville distribution of new digital modulation recognition method, the method to extract generalized fractional Fourier transform, the center is one of the instantaneous amplitude spectral density The maximum amplitude values and fractional lower order Wigner-Ville distribution as an identifying characteristic parameters, and decision tree classifier, to achieve a non-Gaussian noise under digital modulation signal recognition.
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non-Gaussian noise Identification.pdf