该算法从变换域提取全部特征参数，采用决策理论算法，实现调制类型的自动识别。
Based on the characteristic parameters extracted from transform domains, the automatic modulation recognition has been realized by employing decision theory.
该方案利用数字混合信号与常用数字调制信号在信号频谱以及星座点的差异提取特征参数进行自动识别。
In the scheme, a set of feature parameters are extracted from signal spectrum and constellation based on the differences between digital mixed signals and common digital modulation signals.
提出一种基于支持向量机的实际调制信号自动识别新方法。
A new method for modulation classification based on Support Vector Machine (SVM) is presented.
通信信号调制类型的自动识别广泛应用于信号确认、干扰识别、无线电侦听和信号监测等领域。
The automatic identification of the modulation types has been applied to many fields such as signal identification, interference identification, radio interception, signal monitoring, etc.
通信信号调制方式的自动识别和调制参数的自动估计是非协作通信和软件无线电中的重要问题。
Automatic modulation recognition and modulation parameters estimation are key problems in non-cooperative communication systems and Software Defined Radio.
的数字信号调制类型的自动识别已应用在许多领域，包括电子战，监视和威胁分析。
Automatic identification of the digital modulation type of a signal has found applications in many areas, including electronic warfare, surveillance and threat analysis.
针对数字信号调制模式识别问题，提出了运用高阶累积量和二叉树支持向量机(SVM)进行自动识别的算法。
Applying high order cumulants and support vector machines (SVM), an algorithm is proposed for automatic recognition of digital communication signals.
针对数字信号调制模式识别问题，提出了运用高阶累积量和二叉树支持向量机(SVM)进行自动识别的算法。
Applying high order cumulants and support vector machines (SVM), an algorithm is proposed for automatic recognition of digital communication signals.
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