The modulation recognition technology for communication signals based on BP neural networks is studied.
本文研究了基于BP神经网络的通信信号调制体制识别技术。
Experiment result shows that these technologies have better performances for automatic modulation recognition of communication signals.
实验结果表明，该技术拥有较好的通信信号调制体制识别性能。
The classification of modulation types of communication signals is a problem of typical pattern recognition. It involves many perplexing factors.
通信信号调制类型的分类识别是一种典型的模式识别问题，它涉及到很多复杂的因素。
Automatic modulation recognition and modulation parameters estimation are key problems in non-cooperative communication systems and Software Defined Radio.
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。
Modulation Recognition of Communication Signals is an important part in electronic counter measures; it also is a rapidly evolving area of signal analysis.
信号的调制方式识别对于电子对抗和频谱监测都具有极其重要的意义。
Modulation Recognition of Communication Signals is an important part in electronic counter measures; it also is a rapidly evolving area of signal analysis.
信号的调制方式识别对于电子对抗和频谱监测都具有极其重要的意义。
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