基于参考曲线模型和并行非线性最小二乘算法的HPLC-DAD数据分解

Separation of the HPLC-DAD Data Set Based on Reference Curve Model and Parallel Nonlinear Least Square

HPLC-DAD数据分解问题是化学计量学领域的一个重要课题,也是很多其他研究领域的前提和基础。本文基于参考曲线模型,构造了一种三参数的色谱峰参考曲线,并提出了并行非线性最小二乘算法对参考曲线模型(RCM)进行求解。通过仿真实验和HPLC-DAD数据实验,验证了本文提出的方法具有分辨率高、收敛速度快、参数易控制等特点。

The separation of the HPLC-DAD data set is an important issue in the field of chemometrics and is also the foundation of many other researches. By means of the reference curve model, this paper constructs a kind of 3-parameter reference curve for chromatogram peak and proposes an optimization algorithm of parallel nonlinear least square to solve the reference curve model. It is shown via simulations and experiments that compared with other methods, the proposed method has higher resolution, quicker convergence and easy control of parameters.