节点文献
基于奇异熵增量曲率谱的信号降噪方法
A Signal De-noising Method Based on the Curvature of the Increment of Singular Entropy
【摘要】 在利用奇异值分解去噪的算法中,为了实现有效奇异值阶次的自动选取,通过分析奇异熵增量的曲率谱特性,提出了一种基于奇异熵增量曲率谱的确定降噪阶次的方法。分别针对仿真信号和短波接收机实采信号进行了验证试验,结果表明该方法能显著降低噪声,从而提高信噪比,且能够保证降噪后的信号所含信息的完整性。
【Abstract】 In the noise reduction algorithm based on singular value decomposition(SVD),the selection method of the effective de-noising order should be automatic.Through analyzing the characteristics of the curvature of the increment of singular entropy,a new method is presented to determine the de-noising order.Verification tests are taken using the simulation signal and the actual output signal from the receiver front-end respectively.The results show that this method has obviously reduction of the background noise,thus improves the signal-to-noise ratio(SNR),and can guarantee the integrity of the information contained in the signal after noise reduction.
【Key words】 noise reduction; singular value decomposition; the increment of singular entropy; curvature spectrum;
- 【文献出处】 制导与引信 ,Guidance & Fuze , 编辑部邮箱 ,2017年04期
- 【分类号】TN911.7
- 【被引频次】11
- 【下载频次】186