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OALib Journal期刊
ISSN: 2333-9721
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Research on Algorithm of Wavelet Threshold Value De-noising Based on Maximum Criterion of False Alarm Probability
基于虚警概率最大准则的小波阈值去噪算法研究

Keywords: Wavelet transform,Energy-member,Neyman-pearson criterion,SNR
小波变换
,能量元,Neyman-Pearson准则,信噪比

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Abstract:

According to the characteristics of random noise wavelet transform on the different scale and the relationship between of noise Lipschitz and its wavelet transform modulus maxima, the orthogonal wavelet threshold de-noising method is explained, and then a de-noising method based on energy-member and Neyman-Pearson Criterion is proposed. The selection of its threshold is according to the criterion that the detection probability is maximized in given false alarm rate probability, and it is independent on each scale. Numerical simulations show that this de-noising method is effective and excellent.

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