An adaptive single-well stochastic resonance algorithm applied to trace analysis of clenbuterol in human urine.

Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry
Wei WangB Xiang

Abstract

Based on the theory of stochastic resonance, an adaptive single-well stochastic resonance (ASSR) coupled with genetic algorithm was developed to enhance the signal-to-noise ratio of weak chromatographic signals. In conventional stochastic resonance algorithm, there are two or more parameters needed to be optimized and the proper parameters values were obtained by a universal searching within a given range. In the developed ASSR, the optimization of system parameter was simplified and automatic implemented. The ASSR was applied to the trace analysis of clenbuterol in human urine and it helped to significantly improve the limit of detection and limit of quantification of clenbuterol. Good linearity, precision and accuracy of the proposed method ensure that it could be an effective tool for trace analysis and the improvement of detective sensibility of current detectors.

References

Jul 1, 2006·Analytical Chemistry·Gabriel Vivó-Truyols, Peter J Schoenmakers
Aug 28, 2010·Magnetic Resonance Imaging·V P Subramanyam Rallabandi, Prasun Kumar Roy
Jan 12, 2011·Journal of Analytical Toxicology·Jelka PleadinDinka Milić
Mar 15, 2011·Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences·Xiao-Bin ChenTing Yang
Jan 1, 2009·Sensors·Xian-Bin WenFa-Yu Wang

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Methods Mentioned

BETA
enzyme-linked immunosorbent assay

Software Mentioned

ASSR
Matlab
VEGA

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