• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>ASME Artificial Neural Networks in Engineering Conference >Analysis and pattern recognition of HPLC trace organic impurity patterns in phase space
【24h】

Analysis and pattern recognition of HPLC trace organic impurity patterns in phase space

机译：相空间中HPLC痕迹有机杂质图案的分析与模式识别

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A general method for constructing analytical fingerprints and pattern recognition of HPLC (High Performance Liquid Chromatography) trace organic impurity patterns is proposed. The approach considers signals in phase space and accounts for additive (distortion of the relative magnitude of peak signals) and perturbative noise (distortions of the time scale of the trace organic impurity patterns and non-stationarity of signal in time domain) in analyzed data samples. The elaborated method is based on nonlinear models of signals and it enables detection and comparison of similar signal segments realized at different retention times. The classification rate of the method applied to sample chromatographic data remains about 95% even when the number of available data in the training sets are reduced by a factor of 5. The current approach provides a simple yet comprehensive interpretation of the calculated results and, thus, represents a useful technique to be used for practical application in the analysis, monitoring and classification of complex analytical data.
机译：提出了一种用于构建指纹分析和HPLC（高效液相色谱法）微量有机杂质图案模式识别的一般方法。该方法考虑在相空间中的信号和分析的数据样本中占添加剂（峰信号的相对幅度失真）和扰动噪声（微量有机杂质的图案和在时域信号的非平稳的时间标度的扭曲） 。该精细的方法是基于对信号的非线性模型和它使检测和在不同的保留时间来实现类似的信号段的比较。该方法的分类率施加到样品的色谱数据剩余约95％，甚至当由5倍目前的方法提供了一种简单的计算结果和的又全面解释减少在训练集的可用数据的数量，从而，是一项有用的技术，用于在分析中的实际应用，监测和复杂的分析数据的分类。

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