希尔伯特-黄变换
降噪
信号(编程语言)
信噪比(成像)
噪音(视频)
计算机科学
相关系数
分解
模式识别(心理学)
算法
人工智能
白噪声
机器学习
图像(数学)
电信
生态学
生物
程序设计语言
标识
DOI:10.1109/iaeac.2017.8054119
摘要
In the paper, the LMD (Local mean Decomposition) and EMD(Empirical Mode Decomposition) method are selected to denoise the sensible earthquake signal, the paper analyzes resulting conclusions and compares the denoising performance of the two methods. Experimental results show that the LMD and EMD can both achieve capabilities for denoising signals self-adaptively and improve the quality of signals with noise simultaneously. Two parameters, Correlation Coefficient (NC) and Signal to Noise Ratio(SNR), are adopted to evaluate performance of two algorithms. Corresponding data indicates that components obtained in the decomposition of the seismic signal using LMD have higher correlation degree than that using EMD, meanwhile, the filtered signal owns higher SNR value, all above of which show performance of LMD is slightly more superexcellent than that of the traditional EMD in terms of denoising for seismic signals.
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