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调制样式自动识别
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  “调制样式自动识别”译为未确定词的双语例句
     In order to recognize digitally modulated signals with order higher than 4,such as QAM,and to improve the robustness of the recognition method on the AWGN,based on the recognition parameters of the decision-theoretic approach, certain cumulants parameters are added,and the radial basis function(RBF) neural network with those combined parameters is adopted to improve the recognition ability on the digitally modulated signals.
     为识别QAM等阶数高于4的数字调制信号及提高调制识别算法对高斯白噪声(AWGN)的鲁棒性,在决策论识别参数的基础上,增加了高阶统计量识别参数,并利用混合参数的经向基函数(RBF)神经网络实现数字信号调制样式自动识别,提高了对数字调制信号的识别能力.
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  相似匹配句对
     Automatic Recognition Algorithm of Digital Modulation Types
     数字调制方式的自动识别
短句来源
     Automatic Identification of the Digital Signals Modulation Based on the BP Neural Network
     基于BP神经网络的数字调制信号样式自动识别
短句来源
     Automatic Modulation Recognition in the Software Defined Radio Technology
     软件无线电技术的调制方式的自动识别
短句来源
     Simulation of Automatic Recognition of Analogue Modulated Signals
     模拟信号调制方式自动识别仿真
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     Modulate the Signal and Discern Technical Research Automatically in Figure
     数字调制信号自动识别技术
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The automatic identification of signal modulation style is an essential function of the wireless broadcasting station. This paper studies the theory and algorithm of the automatic identification of signal modulation style based on decision theory, discusses the automatic identification of analog digital signal modulation styles, analyses the practical problems during carrying out these algorithms, and provides a new modulation identification method artificial neural net identification to solve these problens....

The automatic identification of signal modulation style is an essential function of the wireless broadcasting station. This paper studies the theory and algorithm of the automatic identification of signal modulation style based on decision theory, discusses the automatic identification of analog digital signal modulation styles, analyses the practical problems during carrying out these algorithms, and provides a new modulation identification method artificial neural net identification to solve these problens.

信号调制样式的自动识别是软件无线电台必须具备的功能之一.主要讨论了基于决策理论的信号调制样式自动识别的基本原理和算法,论述了模拟信号调制样式的自动识别,数字信号调制样式的自动识别方法.也分析了在实现这些算法时会碰到的许多具体的实际问题,提出了能解决这些问题的调制识别新方法——人工神经网络识别法.

The algorithm for automatic recognition of digital signal modulation on the basis of policy_making theory developed by A.K.Nandi and E.E. Azzouz has the advantages of being simple to operate and fit for analysis online. Based on the algorithm above,this paper addressed an algorithm based on OLS RBF neural network. The simulation was made for the modulation recognition and an improved algorithm was proposed to enhance the performance of the method.The better results for signals with Gaussian noise were obtained,whose...

The algorithm for automatic recognition of digital signal modulation on the basis of policy_making theory developed by A.K.Nandi and E.E. Azzouz has the advantages of being simple to operate and fit for analysis online. Based on the algorithm above,this paper addressed an algorithm based on OLS RBF neural network. The simulation was made for the modulation recognition and an improved algorithm was proposed to enhance the performance of the method.The better results for signals with Gaussian noise were obtained,whose SNR are low to 8dB.Seven kinds of digital modulation signals were discussed,including 2ASK,4ASK,2PSK,4PSK(QPSK),2FSK,4FSK and 16QAM.

A.K.Nandi与E.E.Azzouz提出基于决策论的信号调制样式自动识别方法具有简单易行,适合在线分析的优点.本文在该方法的基础上,针对该方法的数字信号调制样式识别进行深入仿真实现,并提出了基于该方法利用正交最小二乘法(OLS)的RBF神经网络实现数字信号调制样式自动识别的方法,最后对计算进行了改进,提高了该方法的识别能力,对SNR为8~20dB的信号识别得到了较好的结果.本文识别的数字信号为2ASK、4ASK、2PSK、4PSK(QPSK)、2FSK、4FSK与16QAM七种信号.

The algorithm for automatic modulation recognition realizes easily and fits to analyze online. Based on it, this paper addressed an algorithm based on orthogonal least squares (OLS) radial basis function (RBF) neural network. Better results were got for the signal with Gaussian noise, whose SNR are 6~30 dB. Seven kinds of digital modulation signal were discussed, they are:2ASK, 4ASK, 2PSK, 4PSK(QPSK), 2FSK, 4FSK and 16QAM.

基于决策论的信号调制样式自动识别方法具有简单易行、适合在线分析的优点,针对一些参数的计算进行了改进,并提出了基于该方法,利用正交最小二乘法(OLS)的径向基函数(RBF)神经网络,实现数字信号调制样式自动识别的方法.提高了该方法的识别能力,对信噪比(SNR)为6~30dB的测试信号识别得到了较好的结果.识别的数字信号为2ASK、4ASK、2PSK、4PSK(QP-SK)、2FSK、4FSK与16QAM.

 
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