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基于AR模型的小波变换在脑电信号消噪中的应用 被引量:1

EEG Signal Denoising Based on AR Mode and Wavelet Transform
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摘要 提出了基于自回归模型(ARM)与小波变换的脑电信号分析方法,并利用他来消除脑电信号中的噪声干扰。小波变换是一种多分辨率的时间尺度分析方法,他能够将信号划分为不同频段的子带信号。根据小波变换的这一特性,对采样获得的脑电信号进行各尺度分解及消噪分析,并给出了各尺度分解结果及消噪结果。利用小波变换能有效去除脑电信号中的噪声干扰。 The article focuses on the method of noise cancellation for EEG signal based on the Autoregressive Model (ARM) and Wavelet Transform (WT). Wavelet transform is a multi - resolution time - frequency analysis method, It can decompose mixed signal into signals at different frequency bands, The EEG signal is analyzed and denoised using WT,then the results are presented respectively. The experiment results show that WT can process noise in the EEG signal effectively.
作者 吴平 陈心浩
出处 《现代电子技术》 2006年第10期28-29,35,共3页 Modern Electronics Technique
关键词 自回归模型 小波变换 脑电信号 消噪 AR models wavelet transform EEG signal denoising
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