Department of Analytical Chemistry, China Pharmaceutical University, Nanjing 211198, China.
Molecules. 2012 Feb 15;17(2):1929-38. doi: 10.3390/molecules17021929.
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.
基于随机共振理论，开发了一种自适应单峰随机共振（ASSR）与遗传算法相结合的方法，以增强弱色谱信号的信噪比。在传统的随机共振算法中，需要优化两个或更多的参数，并且通过在给定范围内的通用搜索来获得适当的参数值。在开发的 ASSR 中，系统参数的优化被简化并自动实现。ASSR 被应用于人体尿液中克伦特罗的痕量分析，这有助于显著提高克伦特罗的检测限和定量限。该方法具有良好的线性、精密度和准确度，确保它可以成为痕量分析和提高现有检测器检测灵敏度的有效工具。
