An object-oriented approach to implementing artificial neural networks is introduced in this article. The networks obtained in this way are highly connected in that they admit edges between nodes in any layers of the network, and dynamic, in that the insertion, or deletion, of nodes, edges or layers of nodes can be effected in a straightforward way. In addition, the activation functions of nodes need not be uniform within layers, and can also be changed within individual nodes. Methods for implementing the feedforward step and the backpropagation technique in such networks are presented here. Methods for creating networks, for implementing the various dynamic properties and for saving and recreating networks are also described.
翻译:本条采用了以目标为导向的实施人工神经网络的方法。以这种方式获得的网络具有高度的连接性,因为它们在网络的任何层次中都接受节点与动态之间的边缘,从而可以直接插入或删除节点、边缘或节点层。此外,节点的激活功能不必在层次内统一,也可以在单个节点内改变。此处还介绍了在这种网络中采用进料前进步骤和回推进技术的方法。还介绍了建立网络、实施各种动态特性以及保存和重新创建网络的方法。