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。
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.
出处
《杭州电子科技大学学报（自然科学版）》
2014年第2期16-19,共4页
Journal of Hangzhou Dianzi University：Natural Sciences
基金
电科院预研基金资助项目(41101040102)
关键词
稀疏性
调制识别
小波变换
sparsity
modulation classification
wavelet transform
