DEDUCTIVE PREDICTION OF MEASUREMENT PRECISION FROM SIGNAL AND NOISE IN LIQUID-CHROMATOGRAPHY
DEDUCTIVE PREDICTION OF MEASUREMENT PRECISION FROM SIGNAL AND NOISE IN LIQUID-CHROMATOGRAPHY
复制标题
DOI：
10.1021/ac00090a013
复制
发表时间：
1994-09-15
影响因子：
7.4
通讯作者：
MATSUDA, R
中科院分区：
文献类型：
--
作者：
HAYASHI, Y;MATSUDA, R
本文的目的是提出和实验证明一个概率理论来预测在高效液相色谱（HPLC）中重复测量的相对标准偏差。HPLC中的基线漂移，通常用1/f噪声表示，用白色噪声和马尔可夫过程的混合随机过程来近似。白色噪声的标准偏差（SD）w和马尔可夫过程的SD m和保留参数rho完全指定了相应随机过程的随机特性，并且通过最小二乘曲线拟合从基线的功率谱密度确定。预测所需的所有参数是噪声参数w、m和rho、信号处理的工作域（这里是积分）、域中目标峰的面积和恒定误差（主要源自样品注入）。每个参数都是由实验数据唯一确定的，理论预测中不涉及任意常数。的预测被证明是优秀的峰与各种面积，高度和宽度在一个很宽的浓度范围内的一些芳香族化合物的HPLC分析。
The aim of this paper is to propose and experimentally prove a probability theory to predict the relative standard deviation of repeated measurements in high-performance liquid chromatography (HPLC). The baseline drift in HPLC, often formulated as 1/f noise, is approximated by a mixed random process comprising white noise and Markov process. The standard deviations (SD), w, of the white noise and the SD, m, and retention parameter, rho, of the Markov process completely specify the stochastic properties of the respective random processes and are determined from the power spectral density of the baseline by least-squares curve fitting. All the required parameters for the prediction are the noise parameters, w, m, and rho, working domain of signal processing (here, integration), area of a target peak in the domain, and constant error (mainly originating from sample injection). Every parameter is uniquely determined from experimental data, and no arbitrary constants are involved in the theoretical prediction. The prediction is shown to be excellent for peaks with various areas, heights, and widths over a wide concentration range in the HPLC analysis for some aromatic compounds.