人工神经网络方法用于脉冲极谱重叠峰解析  

Resolution of Overlapping Pulse Differential Voltammetric Peaks by Use of Artificial Neural Network Approach

作　　者：刘思东[1] 张卓勇[1] 

机构地区：[1]东北师范大学化学系,长春130024

出　　处：《分析化学》1997年第3期249-252,共4页Chinese Journal of Analytical Chemistry

基　　金：国家教委留学回国人员科研启动基金

摘　　要：将人工神经网络（ＡＮＮ）用于脉冲极谱法中Ｐｂ（Ⅱ）和Ｔ１（Ⅰ）重叠信号峰的解析，对神经网络参数的影响及优化作了研究。结果表明，网络的增益、学习速率和动量是影响网络收敛和稳定性的关键参数。本文还将神经网络与偏最小二乘法的计算结果作了比较。An artificial neural network (ANN) was used to resolve overlapping pulse differ- ential voltammetric peaks of Pb(Ⅱ ) al1d Tl(Ⅰ ). The effects of network parameters were in- vestigated. Restults show that the gain, learning rate and momentum are critical for network convergence and stability. A comparison of ANN and partial least squares shows that these two methods are comparable.

关 键 词：人工神经网络 脉冲极谱法 ANN 极谱 

分 类 号：O657.14[理学—分析化学]