为了建立基于光谱的实时监测模型，本文给出了一种基于移动窗口策略的的偏最小二乘算法。
In order to establish real - time model of spectral measurement, a algorithm called Moving Windows Partial Least Squares algorithm is proposed.
将主成分回归(PCR)和偏最小二乘回归(PLSR)的方法引入RBF网络中，提出了分别采用这两种方法确定网络权重的算法。
The Principal Component Regression (PCR) and Partial Least Square Regression (PLSR) methods are applied to determine the weight of the RBF networks with certain good results.
为进一步提高回归算法的色彩校正精度，提出一个基于核偏最小二乘回归的局部迭代算法。
To further improve the calibration precision of the previous regression algorithms, an iterative local algorithm of color calibration based on kernel partial least squares regression is proposed.
证明出，偏最小二乘迭代算法在处理单张数据表成分提取时与主成分分析相同。
Obtained: Partial Least Squares iterative algorithm to handle data sheet leaflet extraction equivalence with Principal Component Analysis.
偏最小二乘是在光谱多元校正中广泛使用的一种算法。
Partial least squares (PLS) is a popular multivariate calibration method applied widely to the multi- component spectral calibration.
本文主要研究内容和研究成果包括两个部分第一部分是研究近期偏最小二乘非线性建模算法。
This paper mainly includes two parts contents and researches. The first part is about study of PLS nonlinear regression algorithm.
本文主要研究内容和研究成果包括两个部分第一部分是研究近期偏最小二乘非线性建模算法。
This paper mainly includes two parts contents and researches. The first part is about study of PLS nonlinear regression algorithm.
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