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作者针对X荧光分析中散射峰干扰和直线拟合精度差等问题 ,采用最优线性联想记忆 (OLAM )神经网络方法解谱 ,研究了无散射峰标准谱的产生和本底干扰问题 .通过用一维高斯分布随机数模拟本底计数产生无散射峰标准谱的方法 ,提高了分析精度 .
In order to solve the problems of scattering peak interference and linear fitting accuracy in X fluorescence analysis, the authors used the optimal linear associative memory (OLAM) neural network method to solve the spectrum and studied the generation of non-scattering peak standard spectrum and background interference problem. One-dimensional Gaussian distribution random number simulation background counting non-scattering peak standard spectrum method to improve the analysis accuracy.