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基于动态光散射数据的粒径分布反演的非负最小二乘截断奇异值分解法。

Nonnegative least-squares truncated singular value decomposition to particle size distribution inversion from dynamic light scattering data.

作者信息

Zhu Xinjun, Shen Jin, Liu Wei, Sun Xianming, Wang Yajing

机构信息

School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255049, China.

出版信息

Appl Opt. 2010 Dec 1;49(34):6591-6. doi: 10.1364/AO.49.006591.

Abstract

The weak symmetry relationship between the relative error and solution norm holds in our developed nonnegative least-squares truncated singular value decomposition method. By using this relationship to specify the optimal regularization parameters, we applied the proposed algorithm to recover particle size distribution from dynamic light scattering (DLS) data. Simulated results and experimental validity demonstrate that the proposed method, which compliments the CONTIN algorithm, might serve as a powerful and simple approach to the inverse problem in DLS.

摘要

在我们开发的非负最小二乘截断奇异值分解方法中,相对误差与解范数之间存在弱对称关系。利用这种关系来指定最优正则化参数,我们将所提出的算法应用于从动态光散射(DLS)数据中恢复粒度分布。模拟结果和实验验证表明,所提出的方法作为CONTIN算法的补充,可能是解决DLS反问题的一种强大而简单的方法。

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