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：本文介绍了一种面向对象的人工神经网络实现方法。通过该方法获得的网络具有高度连通性，即允许网络中任意层节点之间建立连接；同时具有动态性，即能够以直接方式实现节点、连接边或层的插入与删除。此外，节点激活函数在层内不必统一，且可在单个节点内进行更改。本文提出了在此类网络中实现前向传播步骤和反向传播技术的方法，并描述了创建网络、实现多种动态特性以及保存与重建网络的方法。