Nonnegative least-squares truncated singular value decomposition to particle size distribution inversion from dynamic light scattering data
Applied Optics, Vol. 49, Issue 34, pp. 6591-6596 (2010)
http://dx.doi.org/10.1364/AO.49.006591
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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.
© 2010 Optical Society of America
OCIS Codes
(290.3200) Scattering : Inverse scattering
(290.3700) Scattering : Linewidth
(290.5820) Scattering : Scattering measurements
(290.5850) Scattering : Scattering, particles
(300.6170) Spectroscopy : Spectra
ToC Category:
Scattering
History
Original Manuscript: June 21, 2010
Revised Manuscript: October 5, 2010
Manuscript Accepted: October 11, 2010
Published: November 23, 2010
Citation
Xinjun Zhu, Jin Shen, Wei Liu, Xianming Sun, and Yajing Wang, "Nonnegative least-squares truncated singular value decomposition to particle size distribution inversion from dynamic light scattering data," Appl. Opt. 49, 6591-6596 (2010)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-49-34-6591
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