Inversion of tikhonov and truncated singular value decomposition regularization for noisy dynamic light scattering data

2018 ◽  
Vol 26 (9) ◽  
pp. 2269-2279
Author(s):  
王雅静 WANG Ya-jing ◽  
袁 曦 YUAN Xi ◽  
申 晋 SHEN Jin ◽  
窦震海 DOU Zhen-hai ◽  
孙贤明 SUN Xian-ming
2013 ◽  
Vol 40 (6) ◽  
pp. 0608001
Author(s):  
窦震海 Dou Zhenhai ◽  
王雅静 Wang Yajing ◽  
申晋 Shen Jin ◽  
刘伟 Liu Wei ◽  
高珊珊 Gao Shanshan

2018 ◽  
Vol 47 (7) ◽  
pp. 729001
Author(s):  
黄钰 HUANG Yu ◽  
申晋 SHEN Jin ◽  
徐敏 XU Min ◽  
孙成 SUN Cheng ◽  
刘伟 LIU Wei ◽  
...  

2013 ◽  
Vol 42 (11) ◽  
pp. 1324-1328
Author(s):  
于向飞 YU Xiangfei ◽  
杨晖 YANG Hui ◽  
杨海马 YANG Haima ◽  
郑刚 ZHENG Gang ◽  
李军 LI Jun ◽  
...  

Fractal colloid aggregates are studied with both static and dynamic light scattering. The dynamic light scattering data are scaled onto a single master curve, whose shape is sensitive to the structure of the aggregates and their mass distribution. By using the structure factor determined from computer-simulated aggregates, and including the effects of rotational diffusion, we predict the shape of the master curve for different cluster distributions. Excellent agreement is found between our predictions and the data for the two limiting régimes, diffusion-limited and reaction-limited colloid aggregation. Furthermore, using data from several completely different colloids, we find that the shapes of the master curves are identical for each régime. In addition, the cluster fractal dimensions and the aggregation kinetics are identical in each régime. This provides convincing experimental evidence of the universality of these two régimes of colloid aggregation.


2018 ◽  
Vol 13 ◽  
pp. 174830181881360 ◽  
Author(s):  
Zhenyu Zhao ◽  
Riguang Lin ◽  
Zehong Meng ◽  
Guoqiang He ◽  
Lei You ◽  
...  

A modified truncated singular value decomposition method for solving ill-posed problems is presented in this paper, in which the solution has a slightly different form. Both theoretical and numerical results show that the limitations of the classical TSVD method have been overcome by the new method and very few additive computations are needed.


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