A study on the detection of weak photoacoustic signals by stochastic resonance

Improving the detection sensitivity of chromatography by stochastic resonance

This review aims to provide readers with an overview of various methodologies and approaches used to improve sensitivity through stochastic resonance (SR) methods, with special emphasis on applications to improve the detectability of analytes in chromatographic signals.

Detection of trace triclocarban in water sample using solid-phase extraction-liquid chromatography with stochastic resonance algorithm

Based on the theory of stochastic resonance, a new algorithm was presented to enhance the signal-to-noise ratio (SNR) of weak HPLC/UV signals of triclocarban in water samples with a new method for optimizing the system parameters. The method was applied to experimental weak signals of HPLC/ UV, which was embedded in the noise background, and the SNR was enhanced greatly. The algorithm was employed to detect triclocarban residue in water with solid-phase extraction--high-performance liquid chromatography. The limit of detection and the limit of quantification were improved from 10 ng L(-1) and 50 ng L(-1) to 1 ng L(-1) and 5 ng L(9-1), respectively. The results showed an excellent quantitative relationship between concentrations and chromatographic responses.

Improved stochastic resonance algorithm for enhancement of signal-to-noise ratio of high-performance liquid chromatographic signal

Based on the theory of stochastic resonance, an improved stochastic resonance algorithm with a new criterion for optimizing system parameters to enhance signal-to-noise ratio (SNR) of HPLC/UV chromatographic signal for trace analysis was presented in this study. Compared with the conventional criterion in stochastic resonance, the proposed one can ensure satisfactory SNR as well as good peak shape of chromatographic peak in output signal. Application of the criterion to experimental weak signals of HPLC/UV was investigated and the results showed an excellent quantitative relationship between different concentrations and responses.

Stochastic resonance is applied to quantitative analysis for weak chromatographic signal of roxithromycin in beagle dog plasma

Based on the theory of stochastic resonance, the signal to noise ratio (SNR) of HPLC/UV chromatographic signal of roxithromycin is enhanced by cooperation of signal, noise and nonlinear system. A simple new method for the determination of low concentration of roxithromycin in beagle dog plasma is presented. Using signal enhancement by stochastic resonance, this method extends the limit of quantitation from the reported 0.5 to 0.1 microg/ml. During validation of the new method, HPLC/MS was used as a comparison technique. The results indicate that the recovery and low concentrations of roxithromycin in beagle dog plasma were equivalent between the two methods (P>0.05). Stochastic resonance may be a promising tool for improving detection limits in trace analysis.