Single‐well Potential Stochastic Resonance Applied to Quantitative Analysis for Weak Chromatographic Signals of Sudan IV

2007 ◽  
Vol 40 (12) ◽  
pp. 2415-2424 ◽  
Author(s):  
Ying Zhan ◽  
Bingren Xiang ◽  
Wei Zhang ◽  
Shaofei Xie ◽  
Haishan Deng ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Stochastic Resonance ◽  
Single Well ◽  
Sudan Iv

Stochastic resonance is applied to quantitative analysis for weak chromatographic signal of Sudan I

2006 ◽  
Vol 359 (6) ◽  
pp. 620-623 ◽  
Author(s):  
Ye Ye ◽  
Bingren Xiang ◽  
Wei Zhang ◽  
Erxin Shang
Keyword(s):  
Quantitative Analysis ◽  
Stochastic Resonance ◽  
Sudan I

scholarly journals An Adaptive Single-Well Stochastic Resonance Algorithm Applied to Trace Analysis of Clenbuterol in Human Urine

Molecules ◽  
2012 ◽  
Vol 17 (2) ◽  
pp. 1929-1938 ◽  
Author(s):  
Wei Wang ◽  
Suyun Xiang ◽  
Shaofei Xie ◽  
Bingren Xiang
Keyword(s):  
Stochastic Resonance ◽  
Human Urine ◽  
Trace Analysis ◽  
Single Well

Stochastic resonance is applied to quantitative analysis for weak chromatographic signal of glyburide in plasma

2005 ◽  
Vol 550 (1-2) ◽  
pp. 77-81 ◽  
Author(s):  
Wei Zhang ◽  
Bingren Xiang ◽  
Yanwei Wu ◽  
Erxin Shang
Keyword(s):  
Quantitative Analysis ◽  
Stochastic Resonance

scholarly journals The Application of Multiobjective Genetic Algorithm to the Parameter Optimization of Single-Well Potential Stochastic Resonance Algorithm Aimed at Simultaneous Determination of Multiple Weak Chromatographic Peaks

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Haishan Deng ◽  
Shaofei Xie ◽  
Bingren Xiang ◽  
Ying Zhan ◽  
Wei Li ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simultaneous Determination ◽  
Stochastic Resonance ◽  
Peak Shape ◽  
Sudan Dyes ◽  
Data Set ◽  
Multiobjective Genetic Algorithm ◽  
Single Well ◽  
Chromatographic Peaks

Simultaneous determination of multiple weak chromatographic peaks via stochastic resonance algorithm attracts much attention in recent years. However, the optimization of the parameters is complicated and time consuming, although the single-well potential stochastic resonance algorithm (SSRA) has already reduced the number of parameters to only one and simplified the process significantly. Even worse, it is often difficult to keep amplified peaks with beautiful peak shape. Therefore, multiobjective genetic algorithm was employed to optimize the parameter of SSRA for multiple optimization objectives (i.e.,S/Nand peak shape) and multiple chromatographic peaks. The applicability of the proposed method was evaluated with an experimental data set of Sudan dyes, and the results showed an excellent quantitative relationship between different concentrations and responses.

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