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一种新的非高斯分布噪声下的小波去噪方法 被引量:3

A New Wavelet De-noising Method under Non-Gaussian Distribution
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摘要 经典的小波阈值去噪方法在非高斯噪声下往往完全失效,对此提出了一种新的自适应小波信号去噪法.该方法利用最新发展的分位耦合理论,通过建立等价模型,在实施小波变换前将未知噪声信号转换为高斯噪声信号,然后再使用传统小波方法去噪.蒙特卡洛模拟试验结果显示,该方法在非高斯噪声下能极大提高信号去噪效果. The classical wavelet threshold de-noising methods are usually completely ineffective under non-Gaussian noise.This paper presents a new adaptive wavelet de-noising method.The approach uses the newest quantile coupling theory and establishes asymptotic equivalence with two models.It turns the signal with unknown noise into a standard Gaussian noise signal before wavelet de-noising and then uses the classical wavelet de-noising approaches.Monte Carlo simulation results also show that the new approach can greatly improve the de-noising effects.
作者 李翰芳
出处 《湖北工业大学学报》 2011年第2期136-139,共4页 Journal of Hubei University of Technology
关键词 非高斯噪声 分位耦合 小波去噪 蒙特卡洛模拟 non-gaussian noise quantile coupling wavelet de-noising Monte Carlo simulation
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