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.
Highlights
Trace analysis is one of the routine tasks for analytical chemists in various fields of analytical chemistry
When the input signal is fixed, the nonlinear system parameters will directly influence the quality of final output signal and influence the results of quantitative determination
The raw intensities of clenbuterol vary with the spiked concentrations in target samples, the same parameter will be used throughout to keep the quantitative relationship of the output signals
Summary
Trace analysis is one of the routine tasks for analytical chemists in various fields of analytical chemistry. Various smoothing and filtering methods are widely used to improve the signal of interest by reducing the effect of noise [1,2,3,4]. They may result in loss (hopefully negligible) of useful information. Different from these methods, a stochastic resonance (SR) algorithm can amplify the weak signal significantly in a nonlinear system by making use of noise instead of filtering it [5,6,7]. Energy transfer from noise to useful signals will take place when signal and noise cooperate properly within the nonlinear system, i.e., the SR condition is reached, and the SNR of useful signals will be enhanced
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