...
首页> 外文期刊>Chemometrics and Intelligent Laboratory Systems >A new stochastic resonance algorithm to improve the detection limits for trace analysis
【24h】

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

机译:一种新的随机共振算法,可提高痕量分析的检测限

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

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.
机译:基于随机共振理论,提出了一种提高痕量分析的分析检出限的新的随机共振算法(SRA)。在新算法中,随机共振发生在仅由分析信号的固有噪声驱动的双稳态系统中。讨论了系统参数对所提出算法的影响,并研究了参数的优化。通过使用实验色谱和光谱数据集,已证明该方法可以大大提高分析信号的信噪比(SNR),并且可以获得不同浓度及其响应之间的出色定量关系。随机共振可能是扩大仪器线性范围并提高微分析或痕量分析准确性的有前途的工具。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号