In order to improve the alarm accuracy rate in nuclear power station, this paper adopts Wavelet De noising (WD) method based on statistic characteristics and presents a loose parts alarm method.
针对核电站中检测跌落零件误报警率高的问题，本文对带通滤波后的跌落零件冲击信号应用了基于统计特征的小波去噪方法，并给出了去噪后的跌落零件报警方法。
This paper analyzed the characteristic of noise in hyperspectral data deeply, and puts forward a de-noising method based on stationary discrete wavelet transform (SDWT).
文章深入分析了高光谱遥感数据中噪声的特点，提出了一种基于平稳小波变换的改进小波滤噪算法。
Especially to threshold de-noising, a method based on orthogonal wavelet analysis and self-adaptive learning algorithm was proposed here.
特别是对阈值去噪方法，提出了一种基于正交小波变换和自适应学习算法的噪声抑制方法。
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