新认知
计算机科学
机制(生物学)
人工神经网络
阿拉伯数字
光学(聚焦)
人工智能
过程(计算)
模式识别(心理学)
数字系统
比例(比率)
语音识别
时滞神经网络
认识论
量子力学
操作系统
哲学
光学
物理
作者
Kunihiko Fukushima,Sei Miyake,Takayuki Ito
标识
DOI:10.1109/tsmc.1983.6313076
摘要
A recognition with a large-scale network is simulated on a PDP-11/34 minicomputer and is shown to have a great capability for visual pattern recognition. The model consists of nine layers of cells. The authors demonstrate that the model can be trained to recognize handwritten Arabic numerals even with considerable deformations in shape. A learning-with-a-teacher process is used for the reinforcement of the modifiable synapses in the new large-scale model, instead of the learning-without-a-teacher process applied to a previous model. The authors focus on the mechanism for pattern recognition rather than that for self-organization.
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