A linear modulation-based stochastic resonance algorithm applied to the detection of weak chromatographic peaks.

A simple stochastic resonance algorithm based on linear modulation was developed to amplify and detect weak chromatographic peaks. The output chromatographic peak is often distorted when using the traditional stochastic resonance algorithm due to the presence of high levels of noise. In the new algorithm, a linear modulated double-well potential is introduced to correct for the distortion of the output peak. Method parameter selection is convenient and intuitive for linear modulation. In order to achieve a better signal-to-noise ratio for the output signal, the performance of two-layer stochastic resonance was evaluated by comparing it with wavelet-based stochastic resonance. The proposed algorithm was applied to the quantitative analysis of dimethyl sulfide and the determination of chloramphenicol residues in milk, and the good linearity of the method demonstrated that it is an effective tool for detecting weak chromatographic peaks.