Aimed at the ultrasonic signal polluted by noises, which is low in SNR, a method of the ultrasonic signal denoising in wavelet domain based on an improved threshold function was put forward.
针对超声无损检测中超声信号受噪声污染、信噪比不高的情况，提出了一种新的基于改进阈值函数的小波域超声信号去噪方法。
Probed into the two factors of the signal de-noising effect basing on the wavelet transform basing on the analysis of the theory and methods of the wavelet transform: wavelet function and threshold.
在分析小波变换消噪原理和方法的基础上，研究了影响小波变换消噪效果的两个主要因素：小波基函数和阀值。
This article proposed a method to mark denoising threshold from study function of wavelet nerve network in order to improve performance of denoising to signals.
针对某一确定数据采集系统中小波去噪时的阈值选择，提出以小波神经网络加标准信号来标定去噪阈值的方法，从而提高对信号的去噪性能。
This paper achieves noise reduction by using wavelet packet transform, semisoft shrinkage function, Donoho standard deviation estimate and threshold obtain based on statistics.
计算结果表明：变形统计值与变形监测值吻合较好，统计复相关系数较大，估计标准误差较小。
This paper achieves noise reduction by using wavelet packet transform, semisoft shrinkage function, Donoho standard deviation estimate and threshold obtain based on statistics.
计算结果表明：变形统计值与变形监测值吻合较好，统计复相关系数较大，估计标准误差较小。
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