利用离散Hopfield网络分析高等数学教学模式  

Analysis higher mathematics teaching mode based on discrete Hopfield neural network

作　　者：苗鹏[1] 范留军 

机构地区：[1]郑州科技学院基础部,河南郑州450064 [2]郑州科技学院土木建筑与工程学院,河南郑州450064

出　　处：《高师理科学刊》2016年第10期55-57,共3页Journal of Science of Teachers＇College and University

基　　金：2016年度河南省社科联;河南省经团联调研课题项目(SKL-2016-3868)

摘　　要：借助离散Hopfield神经网络对现有高等数学教学模式进行分析讨论,以寻求更加合理的教学模式,从而达到更好的教学目的.将抽象的教学模式转化为计算机语言,进而建立离散Hopfield神经网络,然后对现有几种高等数学教学模式进行分析.运用所建立的离散Hopfield神经网络对给出的实例进行仿真,并做出总结,为今后高等数学教学提供参考.Based on the discrete more reasonable teaching mode Hopfield neural network, studies the teaching mode of higher mathematics, seeks a and achieves better teaching purpose. The abstract teaching is translated into the computer language. Then, design a discrete Hopfield neural network and analyze several existing advanced mathematics teaching mode. The given instance is solved by using the established discrete Hopfield neural network. The summary of the article is given and a reference for later higher mathematics teaching is provided.

关 键 词：离散HOPFIELD神经网络 高等数学 教学模式 实例仿真 

分 类 号：O13[理学—数学] G642.0[理学—基础数学]