Petsche T, Dickinson B W
Dept. of Electr. Eng., Princeton Univ., NJ.
IEEE Trans Neural Netw. 1990;1(2):154-66. doi: 10.1109/72.80228.
Relationships between locally interconnected neural networks that use receptive field representations and trellis or convolutional codes are explored. A fault tolerant neural network is described. It is patterned after the trellis graph description of convolutional codes and is able to tolerate errors in its inputs and failures of constituent neurons. This network incorporates learning, which adds failure tolerance; the network is able to modify its connection weights an internal representation so that spare neurons can replace neurons which fail. A brief review of trellis-coding concepts is included.
探索了使用感受野表示的局部互连神经网络与网格或卷积码之间的关系。描述了一种容错神经网络。它是仿照卷积码的网格图描述构建的，能够容忍输入中的错误和组成神经元的故障。该网络包含学习功能，这增加了容错能力；网络能够修改其连接权重和内部表示，以便备用神经元可以替代发生故障的神经元。文中还包括了对网格编码概念的简要回顾。
