Linear Modulated Stochastic Resonance Algorithm Applied to Determination of Thidiazuron Residue in Water Using Stochastic Resonance

Abstract

The newly proposed linear modulated stochastic resonance algorithm (LSRA) was used to amplify and detect the weak chromatographic peaks of thidiazuron. The output chromatographic peak is often distorted when using the traditional 3095 stochastic resonance algorithm because of the existence of strong noise. In LSRA, the distortion of the output peak can be corrected by introducing a linear force into the nonlinear system. A two-step optimization method was proposed to give attention to both the signal-to-noise ratio and the peak shape of output signal. The weak chromatographic peaks of thidiazuron can be amplified significantly and the distortion of the output peaks can be corrected using LSRA. The algorithm was used to detect thidiazuron residue in water with solid phase extraction-high performance liquid chromatography. The limit of detection and limit of quantification were improved to 2.5 ng/l and 10 ng/l, respectively.