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   调制类型识别 的翻译结果: 查询用时:0.267秒
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调制类型识别
相关语句
  modulation type recognition
     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
  “调制类型识别”译为未确定词的双语例句
     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
     This paper studies the use of wavelet transform to distinguish MPSK signals.
     本文对小波变换应用于MPSK信号的调制类型识别进行了研究,并提出了一种基于小波变换的提取MPSK信号相位信息的方法。
短句来源
     The signal modulation pattern identification and accurate parameter estimation algorithm for monopulse,LFM and phase coded radar signals are studied. Then,their hardware implementation platform is established with TMS320C6713.Testing results show that this method can deal with two simultaneously arriving signals.
     研究了单脉冲、线性调频与相位编码雷达信号的调制类型识别与高精度参数估计算法,基于TMS320C6713搭建的硬件平台,完成了两个同时到达信号的高精度参数估计。
短句来源
     The analysis shows that the magnitude of time-frequency distribution is closely related with the structure of phase of the signal. So, by the detection of the characteristic magnitude, the discontinuities can be accurately located, and their values can also be estimated.
     分析表明信号时频表示的幅度能够直观地反映出其相位的变化,因此通过对时频分布峰值特征的检测可以准确定位频率跳变时刻,并能够定量的了解这些参数的变化,从而为信号的相位调制类型识别提供帮助。
短句来源
     With the problem of identifying modulation types in electronic warfare in mind,a novel maximum likelihood(ML) modulation classification algorithm is presented in the wavelet transform domain.
     针对电子战领域中的调制类型识别问题,提出了一种把通信信号变换到小波域下的最大似然调制分类算法.
短句来源
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  相似匹配句对
     Automatic Recognition of Modulation Schemes Based on Transform Domains
     基于变换域的调制类型自动识别
短句来源
     Automatic Modulation Recognition of TTC Signals of Satellite
     卫星测控信号的调制类型自动识别算法
短句来源
     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
     Automatic Recognition of Modulation Schemes Under Non-AWGN Channel
     非AWGN环境下调制类型自动识别
短句来源
     Palaeosols:Types and Recognition
     古土壤的类型识别标志
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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-style recognition of radar signals is an important aspect in electronic warfare. A hybrid RBF training algorithm combined with artificial immune clustering and evolutionary programming is proposed and applied in modulation-style recognition of radar signals. In the algorithm, artificial immunology for data clustering was used to adaptively determine the amount and the positions of initial RBF centers according to input data set. Then the RBF network was trained with evolutionary programming. Computer...

Modulation-style recognition of radar signals is an important aspect in electronic warfare. A hybrid RBF training algorithm combined with artificial immune clustering and evolutionary programming is proposed and applied in modulation-style recognition of radar signals. In the algorithm, artificial immunology for data clustering was used to adaptively determine the amount and the positions of initial RBF centers according to input data set. Then the RBF network was trained with evolutionary programming. Computer simulations demonstrate that the recognition rate of different analog modulation styles designed by the RBF network in this method is high.

对敌方雷达信号调制类型的识别是电子对抗的一个重要方面。采用了一种基于人工免疫聚类和进化规划的混合算法设计径向基函数(RBF)网络,并将其应用于雷达信号调制类型的自动识别。该算法首先利用一种实现数据聚类的人工免疫机制,根据输入数据集合自适应地确定RBF网络初始中心的数量和位置,之后采用进化规划训练RBF网络。仿真实验表明,采用这种方法设计的RBF网络对各种模拟调制信号的调制类型达到了较高的识别精度。

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。

 
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