Abstract
In photon correlation spectroscopy (PCS), there are relatively few cases where there is prior knowledge that the scattered field autocorrelation function contains only one component. Even in these favorable cases, every data analysis procedure should have the capability of accounting for extra unexpected components, e.g., due to instrumentation problems, aggregation, strongly scattering impurities, or even an important undiscovered effect. Often the main purpose of the experiment is to study polydispersity anyway. The first-order correlation function can often be approximated as a linear superposition of apparently independent contributions, yielding a Freaholm integral equation of the first kind,
where K(λ, tj) is known [e.g., exp(-λtj)], and s(λ) (e.g., a velocity or particle radius distribution) is to be estimated from the data γj, containing unknown noise components εj.
Keywords
- Photon Correlation Spectroscopy
- Photon Correlation Spectroscopy
- Nonnegativity Constraint
- European Molecular Biology Laboratory
- Parsimonious Solution
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 1983 Springer-Verlag Berlin Heidelberg
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Provencher, S.W. (1983). A General-Purpose Constrained Regularization Method for Inverting Photon Correlation Data. In: Schulz-DuBois, E.O. (eds) Photon Correlation Techniques in Fluid Mechanics. Springer Series in Optical Sciences, vol 38. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39493-8_32
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DOI: https://doi.org/10.1007/978-3-540-39493-8_32
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