A new stochastic resonance algorithm to improve the detection limits for trace analysis

Based on the stochastic resonance theory, a new stochastic resonance algorithm (SRA) to improve analytical detection limits for trace analysis is presented. In the new algorithm, stochastic resonance takes place in a bistable system driven only by the inherent noise of an analytical signal. The effect of the system parameters on the proposed algorithm is discussed and the optimization of parameters is studied. By using experimental chromatographic and spectroscopic data sets, it is proven that the signal-to-noise ratio (SNR) of the analytical signal can be greatly enhanced by the method, and an excellent quantitative relationship between different concentrations and their responses can be obtained. Stochastic resonance may be a promising tool to extend instrumental linear range and to improve the accuracy of micro- or trace analysis.