摘要
基于经验模态分解方法的基本思想,本文利用噪声曲率曲线与信号曲率曲线的离散Frechet距离有显著差异这一特性,提出了一种新的滤波法。采用该方法对模拟数据进行分析,结果表明新的滤波法是一种有效的去噪方法,与传统的经验模态分解(Empirical Mode Decomposition, EMD)方法相比,该方法能够实现对信号的去噪,具有较高的信噪比。该方法可有效地削弱噪声对信号的影响,进而从含噪信号中提取出有用信息。
Based on the basic idea of empirical mode decomposition method, this paper presents a new fil-tering method by using the significant differences between the noise curvature curve and the dis-crete Frechet distance of the signal curvature curve. Using this method to analyze the simulation data, the results show that the new filtering method is an effective denoising method. Compared with the traditional empirical mode decomposition (EMD) method, this method can denoise the signal and have high signal to noise ratio. This method can effectively reduce the influence of noise on the signal, then extract useful information from the noisy signal.
出处
《应用数学进展》
2017年第7期881-891,共11页
Advances in Applied Mathematics
