2) quantum learning
量子学习
1.
A quantum learning algorithm is proposed and its convergence property is discussed.
本文介绍了与量子神经网络相关的量子计算基础,描述了一种量子神经元模型,提出了一种量子学习算法,通过理论推导和仿真证明了算法的收敛性并给出了几种收敛特性曲线。
3) learning model
学习模型
1.
Research of ERP system learning model based on E-learning;
基于E-learning的ERP系统学习模型研究
2.
Research of hierarchy online learning model and learning control;
多层次网络学习模型与学习控制研究
3.
The first fuzzy model named prior model is built by using expert knowledge and skilled operating experiences of the flash furnace(that is, fuzzy IF THEN rules); the second fuzzy model named learning model is built by using adaptive fuzzy neural network system.
一种方法是利用专家知识和操作经验(即IF THEN规则)建立闪速炉的先验模型 ;另一种方法是利用自适应模糊神经网络方法建立闪速炉的学习模型。
4) Model learning
模型学习
1.
Based on this,a neural network learning algorithm,E H,is proposed,which combines error driven s task learning and Hebbian rule s model learning.
基于此 ,提出了一种将误差驱动的任务学习与Hebbian规则的模型学习相结合的E H方法 。
补充资料：单量子阱(见量子阱)
单量子阱(见量子阱)
single quantum well
单且子阱sillgle quantum well见量子阱。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条