用于多普勒回波去噪的双重指数型阈值函数
发布时间：2018-07-17 16:16
【摘要】：针对小波阈值去噪传统方法所使用的阈值函数存在不连续或估计的小波系数存在偏差导致去噪效果不理想的问题,提出了双重指数型阈值函数。该阈值函数呈双重指数形式,不是分段函数,含有一个调控参数控制估计的小波系数向分解的小波系数或0逼近的速度,以阈值和分解的小波系数的比值是否大于1判定估计的小波系数的逼近方向。仿真结果表明在对多普勒回波的去噪过程中,使用双重指数型阈值函数的去噪结果优于使用传统阈值函数的去噪结果。
[Abstract]:In order to solve the problem that the threshold function used in traditional wavelet threshold denoising method is discontinuous or the estimated wavelet coefficients are deviated and the denoising effect is not ideal, a double exponential threshold function is proposed. The threshold function is a double exponential function, not a piecewise function, and contains a regulating parameter to control the speed of the wavelet coefficients being decomposed to the decomposed wavelet coefficients or zero approximation. The approximation direction of the estimated wavelet coefficients is determined by whether the ratio of the threshold and the decomposed wavelet coefficients is greater than 1. The simulation results show that the double exponential threshold function is better than the traditional threshold function in the denoising process of Doppler echo.
【作者单位】： 西安机电信息技术研究所;机电动态控制重点实验室;
【分类号】：TN911.4
[Abstract]:In order to solve the problem that the threshold function used in traditional wavelet threshold denoising method is discontinuous or the estimated wavelet coefficients are deviated and the denoising effect is not ideal, a double exponential threshold function is proposed. The threshold function is a double exponential function, not a piecewise function, and contains a regulating parameter to control the speed of the wavelet coefficients being decomposed to the decomposed wavelet coefficients or zero approximation. The approximation direction of the estimated wavelet coefficients is determined by whether the ratio of the threshold and the decomposed wavelet coefficients is greater than 1. The simulation results show that the double exponential threshold function is better than the traditional threshold function in the denoising process of Doppler echo.
【作者单位】： 西安机电信息技术研究所;机电动态控制重点实验室;
【分类号】：TN911.4
【共引文献】
相关期刊论文 前10条
1 周健;龙兴武;;小波分析在激光多普勒信号处理中的应用[J];强激光与粒子束;2010年12期
2 董林W，
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