原子吸收光谱仪有多种校准方式,因为样品浓度和吸光度之间有线性关系及非线性关系,如果在具体分析中是线性关系就使用线性校准,,如果在具体分析中是非线性关系就使用非线性校准.
系统选用背光源照明，采用非线性校准及查找圆边的方法对采集到的图像进行测量。
N on linear calibration and finding circle edge were introduced to measure the images acquired.
探讨了采用神经网络校准仪器非线性的方法，并用递推预报误差算法训练神经网络。
The method of calibrating the nonlinearity of the instrument by using nervous network is investigated. The nervous network is trained by recurrence forecast error algorithm.
将合成校准光谱和实验测得的光谱进行非线性最小二乘拟合，得到了不同温度下标准气体CO浓度。
With the nonlinear least squares fit between measured spectra and calibration spectra, standard gas concentrations of co at different temperatures are obtained.
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