摘要
针对前向离散型单隐层Madaline网络建立了以矩阵为基础的数学模型,结合高维空间超平面划分理论,通过对表示样本的矩阵与代表网络性质的矩阵进行分析运算,在输入样本维度较低的情况下给出了Madaline网络的批量学习方法。该方法可有效地解决离散数据的两类分类问题。
In this paper,a matrix computing-based mathematic model was established for the feedforward discrete Madaline network with one hidden layer.By analyzing the matrix representing samples and the matrix representing attributes of the network,and combining the hyperplane division theory in high dimensional space,a batch learning method was proposed for Madaline network with the input of lower dimensional samples.This method can effectively solve the problem of two-category classification of discrete data.
出处
《计算机应用》
CSCD
北大核心
2012年第12期3339-3342,共4页
journal of Computer Applications
