| 基于小波系数稀疏性的数字调制样式识别 |
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| 引用本文： | 赵知劲,胡俊伟.基于小波系数稀疏性的数字调制样式识别[J].杭州电子科技大学学报,2014(2):16-19. |
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| 作者姓名： | 赵知劲 胡俊伟 |
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| 作者单位： | 杭州电子科技大学通信工程学院,浙江杭州310018 |
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| 基金项目： | 电科院预研基金资助项目（41101040102） |
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| 摘 要： | 采用小波变换提取信号突变点信息,根据归一化前后数字调制信号小波系数稀疏性的不同特点,提出两个稀疏度参数和一种利用信号稀疏特性的类间调制样式识别算法。仿真结果表明,在低信噪比时方法比传统小波变换方法具有更高的正确识别率,算法复杂度低,且不需要码元同步。
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| 关 键 词： | 稀疏性 调制识别 小波变换 |
Digital Modulation Classification Using Sparsity of Wavelet Coefficient |
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| Zhao Zhijin,Hu Junwei.Digital Modulation Classification Using Sparsity of Wavelet Coefficient[J].Journal of Hangzhou Dianzi University,2014(2):16-19. |
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| Authors: | Zhao Zhijin Hu Junwei |
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| Affiliation: | (School of Communication Engineering, Hangzhou Dianzi University, Hangzhou Zhejiang 310018, China) |
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| Abstract: | The transient characteristics of different modulated signals are extracted by using wavelet transform. Because the coefficients of wavelet transform have different characteristics whether the signal is normalized or not,two feature parameters and a new method of inter modulation classification algorithm using the sparse features of the signal are proposed. Simulation results show that the new method has the higher classification probability in low SNR and the lower complexity than classical method,and does not need code synchronization. |
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| Keywords: | sparsity modulation classification wavelet transform |
| 本文献已被 CNKI 维普 等数据库收录！ |
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