Symbols Language Neural Networks Performance
作者:
Frank Van Der Velde,
期刊:
Connection Science
(Taylor Available online 1995)
卷期:
Volume 7,
issue 3-4
页码: 247-280
ISSN:0954-0091
年代: 1995
DOI:10.1080/09540099509696193
出版商: Taylor & Francis Group
关键词: Symbols Language Neural Networks Performance
数据来源: Taylor
摘要:
An implementation of non-regular symbol manipulation with neural networks is presented. In particular, it is shown how a context-free language can be produced with neural networks. The rules of the language are stored as patterns in an attractor neural network. Another such network is used as a working memory, which can be enlarged without changing the production system itself. As a result, the competence of symbol manipulation with neural networks equals that of classical non-regular production systems. In actual behaviour (performance), however, there are differences between the systems, which shows the importance of implementation in the generation of rule-like behaviour.
点击下载:
PDF (510KB)
返 回