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首页 » 语音识别 » 本文分析了用经验模态分解( Empirical Mode Decomposition ,EMD) 方法处理非平稳噪声信号的基本原理 , 并利用 EMD 方法...

本文分析了用经验模态分解( Empirical Mode Decomposition ,EMD) 方法处理非平稳噪声信号的基本原理 , 并利用 EMD 方法...

于 2022-03-07 发布 文件大小:97.11 kB
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本文分析了用经验模态分解( Empirical Mode Decomposition ,EMD) 方法处理非平稳噪声信号的基本原理 , 并利用 EMD 方法有效地消除了高斯白噪声对瞬态散射回波的干扰. 文中以一人工合成瞬态回波为例 ,对本方法的有 效性作了检验.-This paper analyzes the use of empirical mode decomposition (Empirical Mode Decomposition, EMD) method to deal with non-stationary noise signals in the basic principles and methods of use of EMD effectively eliminates the Gaussian white noise on the transient scattering echo interference. Text in one artificial Synthesis of transient echoes as an example of the effectiveness of this method were tested.

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