A study of dynamic knowledge representation based on neural networks

被引：0
|
作者：
Pan, H [1 ]
Zhong, L [1 ]
Yuan, JL [1 ]
机构：
[1] Wuhan Univ Technol, Sch Comp Sci & Technol, Wuhan 430070, Peoples R China
来源：
2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS | 2002年
关键词：
dynamic competitive learning; cluster knowledge representation; neural network;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The competitive learning technique is a well-known algorithm used in neural networks, which classifies the input vectors, so that the vectors (samples) belonging to the same class have similar characteristics. Dynamic competitive learning is an unsupervised learning technique, which consists of two additional parts related to conventional competitive learning: a method of generation of new units within a cluster and a method of generating new clusters. The model is capable for the high-level storage of complex data structures, whose classification include exception handling.
引用
收藏
页码：126 / 128
页数：3
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