摘要
本文提出一种基于人工神经元模型的新方法对混合物进行定量分析。在模型的训练过程中运用了最小均方算法,其优点是收敛速度很快,可以用于实验室数据处理。本文还用模拟数据讨论了参数选择和分离度的影响,用实验数据检验了新方法。
A novel method which is based on the model of artificial neuron was proposed for quantitative analysis of mixtures. Least mean squares (LMS) algorithm was used in the training procedures. The merit of the algorithm is the fast convergence and it can be used for data analysis in laboratories. The effect of the selected parameters and the resolution was investigated by using simulated data and the new method was tested by using real data.
出处
《分析化学》
SCIE
EI
CAS
CSCD
北大核心
1992年第11期1327-1329,共3页
Chinese Journal of Analytical Chemistry
关键词
人工神经元
最小均方算法
定量分析
Artificial neuron
Quantitative analysis
Least mean squares
