针对基于特征值的谱感知算法在脉冲噪声的环境下感知性能不佳的问题,分析矩阵全部的特征值,引入矩阵特征值的几何均值,提出了基于分数低阶协方差矩阵的最大特征值与特征值几何均值之差(difference between maximum eigenvalue and geome...针对基于特征值的谱感知算法在脉冲噪声的环境下感知性能不佳的问题,分析矩阵全部的特征值,引入矩阵特征值的几何均值,提出了基于分数低阶协方差矩阵的最大特征值与特征值几何均值之差(difference between maximum eigenvalue and geometric mean of eigenvalue,DMGM)的频谱感知算法。选择了Alpha稳定分布噪声模拟脉冲噪声环境,理论分析与仿真实验结果表明,在不增加算法复杂度的前提下,DMGM算法与其他算法相比,更适用于脉冲噪声环境,在低信噪比条件下具有更好的感知性能。展开更多
Speckle decorrelation algorithm is a method using decorrelation curves to estimate the distance between two neighbor- ing ultrasound images. In this paper, we propose a new method to obtain specific decorrelation curv...Speckle decorrelation algorithm is a method using decorrelation curves to estimate the distance between two neighbor- ing ultrasound images. In this paper, we propose a new method to obtain specific decorrelation curves for distance estimation. First, several datasets of synthetic ultrasound （US） images are obtained by scanning different scatters. Second, based on the US datasets, we compute low-order moments and the elevational decorrelation curves. Finally, low-order moments are used to classify different scattering conditions. The suitable decorrelation curves can be acquired when the scattering style has been determined. With these steps, the relationship between low order moments and the decor- relation curves is established by the scattering conditions. This relationship proves to be efficient and applicable in the experiment section. The decorrelation curves chosen according to the rela- tionship also perform well in the distance estimation test.展开更多
文摘针对基于特征值的谱感知算法在脉冲噪声的环境下感知性能不佳的问题,分析矩阵全部的特征值,引入矩阵特征值的几何均值,提出了基于分数低阶协方差矩阵的最大特征值与特征值几何均值之差(difference between maximum eigenvalue and geometric mean of eigenvalue,DMGM)的频谱感知算法。选择了Alpha稳定分布噪声模拟脉冲噪声环境,理论分析与仿真实验结果表明,在不增加算法复杂度的前提下,DMGM算法与其他算法相比,更适用于脉冲噪声环境,在低信噪比条件下具有更好的感知性能。
基金Supported by the National Basic Research Program of China(2011CB707900)
文摘Speckle decorrelation algorithm is a method using decorrelation curves to estimate the distance between two neighbor- ing ultrasound images. In this paper, we propose a new method to obtain specific decorrelation curves for distance estimation. First, several datasets of synthetic ultrasound （US） images are obtained by scanning different scatters. Second, based on the US datasets, we compute low-order moments and the elevational decorrelation curves. Finally, low-order moments are used to classify different scattering conditions. The suitable decorrelation curves can be acquired when the scattering style has been determined. With these steps, the relationship between low order moments and the decor- relation curves is established by the scattering conditions. This relationship proves to be efficient and applicable in the experiment section. The decorrelation curves chosen according to the rela- tionship also perform well in the distance estimation test.
