title: An adaptive single-well stochastic resonance algorithm applied to trace analysis of clenbuterol in human urine.
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.
authors.affiliation: Department of Analytical Chemistry, China Pharmaceutical University, Nanjing 211198, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.forename: Suyun
authors.initials: S
authors.lastname: Xiang
authors.forename: Shaofei
authors.initials: S
authors.lastname: Xie
authors.forename: Bingren
authors.initials: B
authors.lastname: Xiang
mesh_terms: D000318:Adrenergic beta-Agonists / Q000652:urine*; D000465:Algorithms; D002976:Clenbuterol / Q000652:urine*; D006801:Humans; D057230:Limit of Detection; D013269:Stochastic Processes
chemical_list: D000318:Adrenergic beta-Agonists; D002976:Clenbuterol