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    题名 作者 年代 出处 被引量
1基于SCA的欠定跳频网台分选方法显示文摘针对组网跳频信号在欠定条件下网台分选效果不佳的问题,提出了一种基于稀疏成分分析(sparse component analysis,SCA)的欠定跳频网台分选方法。在估计混合矩阵时,首先利用观测信号的实部与虚部方向一致性检测时频单源点,在采用S变换构造时频比矩阵的基础上,利用方差法实现了混合矩阵估计;在源信号恢复时,利用改进的子空间投影法得到源信号的时频域分离,最后可通过S逆变换得到时域分离信号,从而实现了欠定条件下的跳频网台分选。仿真结果表明,该方法有效实现了混合跳频信号在欠定条件下的网台分选且适用于跳频同步或异步组网方式,提高了分选性能和抗噪性能。唐宁 郭英 张坤峰 2017系统工程与电子技术2017,39,12:4
2Unsupervised robust adaptive filtering against impulsive noise显示文摘An implementation of adaptive filtering, composed of an unsupervised adaptive filter (UAF), a multi-step forward linear predictor (FLP), and an unsupervised multi-step adaptive predictor (UMAP), is built for suppressing impulsive noise in unknown circumstances. This filtering scheme, called unsupervised robust adaptive filter (URAF), possesses a switching structure, which ensures the robustness against impulsive noise. The FLP is used to detect the possible impulsive noise added to the signal. If the signal is 'impulse-free', the filter UAF can estimate the clean signal. If there exists impulsive noise, the impulse corrupted samples are replaced by predicted ones from the FLP, and then the UMAP estimates the clean signal. Both the simulation and experimental results show that the URAF has a better rate of convergence than the most recent universal filter, and is effective to restrict large disturbance like impulsive noise when the universal filter fails.Tao Ma Jie Chen Wenjie Chen Zhihong Peng 2012Journal of Systems Engineering and Electronics2012,23,1:1
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