A neural network model with dynamical compensating capability is analyzed. During the training of this network model, we apply the principle of dynamic error back-propagation.
本文分析了一种动态补偿神经网络模型，模型的训练利用反向传播原理实现。
参考来源 - 基于系统辨识的神经网络学习算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
Introduce the Error Back-Propagation algorithm.
介绍了误差逆传播算法。
With the back-propagation algorithm in hand, we can turn to our puzzle of identifying the language of source code samples.
在掌握了反向传播算法后，可以来看我们的识别源代码样本语言的难题。
where j varies over all the output nodes that receive input from n. Moreover, the basic outline of a back-propagation algorithm runs like this.
这里每个从 n 接收输入的输出节点 j 都不同。 关于反向传播算法的基本情况大致如此。
应用推荐