...采用传感器输出的最大值、相对值和响应时间作为特征参数,建立了单层感知器和反向传播神经网络(Back-Propagation Neural Network,BPNN),用20例样本中的前16例训练网络,再用训练好的神经网络去识别剩余的4例样本。
基于4个网页-相关网页
本文提出了一种基于主分量分析法和反向传播神经网络的图像识别方法，并详细阐述了这种方法的具体实现过程。
Dynamic and static mapping techniques are introduced here as the qualitative methods while statistical methods, inverse calculation and principle component analysis are introduced a.
反向传播人工神经网络对正常肝和脂肪肝的识别率均为100%。
The accuracy rate of neural network was 100% both for normal liver and fatty liver.
以人工神经网络的前馈型网络为基础结构，基于反向传播算法进行学习和训练来拟和证券价格指数的运动趋势。
In this model, back propagation algorithm based on forward networks was conducted to learn information of historical data and to train the network weights.
应用推荐