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   数字调制类型 的翻译结果: 查询用时:0.197秒
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数字调制类型
相关语句
  digital modulation types
     Threshold and training parameters are not needed with this method,but can recognize higher-order digital modulation types.
     该方法无需设置判决门限,也无需进行参数训练,且可以识别大于四阶的数字调制类型.
短句来源
  “数字调制类型”译为未确定词的双语例句
     Digital modulation type recognition using neural network based on discrete searching
     基于离散搜索神经网络的数字调制类型识别
短句来源
     Its successful recognition rate is over 97 % at the signal-to-noise ratio ( SNR) of not less than 8 dB. Its features are smooth identification without the need for any prior knowledge of the modulation signal, many identification types for digital modulation, high successful recognition rate, automatic classification and identification and real-time identification.
     在SNR≥ 8dB时,该分类器的正确识别率达到97%以上,其特点是,识别无需任何先验知识,识别的数字调制类型多,识别的正确率高,达到了自动分类识别的目的,并有利于实现识别的实时化。
短句来源
     This paper proposes a new method based on received signal of fourth and sixth order cumulants for classification digital modulation signals. The method is illuminated and verified. Using computer simulation,recognition of the 2ASK/2PSK,4ASK,8ASK,4PSK,8PSK and 16SQAM signals is efficient.
     本文提出了以接收信号的四、六阶累量为特征来识别数字调制信号,文中进行了理论推导,并做了仿真验证该方法的可行性,实现了对2A SK/2PSK、4A SK、8A SK、4PSK、8PSK、16SQAM等数字调制类型识别。
短句来源
     Automatic identification of the digital modulation type of a signal has found applications in many areas, including electronic warfare, surveillance and threat analysis.
     信号的数字调制类型识别在电子战、电子侦察和威胁告警等领域有广泛的应用前景。
短句来源
  相似匹配句对
     Digital modulation type recognition using neural network based on discrete searching
     基于离散搜索神经网络的数字调制类型识别
短句来源
     Digital Modulation Techniques
     数字调制解调技术
短句来源
     Digital Processing of Modulation and Demodnlation
     调制解调的数字实现
短句来源
     DIGIT
     数字
短句来源
     FIGURE
     数字
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  digital modulation types
Schematics have also been provided for simulation of mixers when driven by digital modulation types such as GSM or CDMA.
      


Automatic modulation mode recognition of communication signals has found wide application areas, and it is very important for a military software radio interception receiver. A hierarchical neural network classifier is designed for identifying nine modulation types based on the research on the characteristic set of digital modulation mode recognition. Its successful recognition rate is over 97 % at the signal-to-noise ratio ( SNR) of not less than 8 dB. Its features are smooth identification without the need...

Automatic modulation mode recognition of communication signals has found wide application areas, and it is very important for a military software radio interception receiver. A hierarchical neural network classifier is designed for identifying nine modulation types based on the research on the characteristic set of digital modulation mode recognition. Its successful recognition rate is over 97 % at the signal-to-noise ratio ( SNR) of not less than 8 dB. Its features are smooth identification without the need for any prior knowledge of the modulation signal, many identification types for digital modulation, high successful recognition rate, automatic classification and identification and real-time identification. The simulation results verify the advantages of this method.

自动调制方式识别应用范围广泛,对于军用软件无线电侦察接收机更具有十分重要的意义。研究了数字调制方式识别的特征集,在此基础上针对BPSK、QPSK、8PSK、16QAM、2FSK、4FSK、8FSK、2ASK、4ASK共9种调制类型识别问题,设计了一种分层结构的神经网络分类器。在SNR≥ 8dB时,该分类器的正确识别率达到97%以上,其特点是,识别无需任何先验知识,识别的数字调制类型多,识别的正确率高,达到了自动分类识别的目的,并有利于实现识别的实时化。仿真结果表明了此方法的优越性。

Modulation identification has important applications in communication surveillance and countermeasure.In order to identify the digital modulation types by the wavelet transform,the Quasi-Haar wavelet is put forward as a choice which has better localization characteristics in frequency domain than that of Haar wavelet. The feasibility of using the sinusoidal Quasi-Haar wavelet to classify MPSK and MFSK is theoretically analyzed,that is the relationship between the amplitude of wavelet coefficients and the frequency...

Modulation identification has important applications in communication surveillance and countermeasure.In order to identify the digital modulation types by the wavelet transform,the Quasi-Haar wavelet is put forward as a choice which has better localization characteristics in frequency domain than that of Haar wavelet. The feasibility of using the sinusoidal Quasi-Haar wavelet to classify MPSK and MFSK is theoretically analyzed,that is the relationship between the amplitude of wavelet coefficients and the frequency or phase changes is deduced, and the simulation is made to the modulation identifier based on the proposed Quasi-Haar wavelet. Both the theoretical analysis and the simulation results show that the sinusoidal quasi-Haar wavelet not only can be used in modulation identification of communication signals, but also has better anti-noise performance under the appropriate SNR.

调制识别在通信侦察和通信对抗中有着重要应用。为了利用小波变换进行数字调制的类型识别,提出了具有比Haar小波更好频率局域化特征的类Haar小波概念,从理论上论证了正弦型类Haar小波用于MPSK和MFSK信号调制识别的可行性,详细推导了小波系数幅度与相位跳变或频率跳变之间的关系,并对分类识别器进行了仿真。理论和仿真结果均表明,在一定信噪比条件下,正弦型类Haar小波不仅能用于通信信号的调制识别,且具有比Haar小波更好的抗噪性能。

A new method for digital modulation recognition based on cyclic variance of normalized-centered absolute value is proposed.Threshold and training parameters are not needed with this method,but can recognize higher-order digital modulation types.Simulation results indicate that the proposed method has higher recognition rate in moderate signal to noise ratio.

提出了将瞬时信息的零均值归一化绝对值方差循环化的方法,用以识别数字调制信号.该方法无需设置判决门限,也无需进行参数训练,且可以识别大于四阶的数字调制类型.仿真实验结果表明,该方法在一定信噪比下对MASK、MPSK和MQAM有较高的识别率.

 
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