| Abstract |
|
This paper presents a neuro-fuzzy system by using the Kohonen's self-organizing feature map algorithm, not only for its vector quantization feature, but also for its topological property. This property prevents the proposed neuro-fuzzy system from suffering from a drawback like any of the conventional clustering-algorithm-based fuzzy systems, i.e. the optimal number of clusters or some kind of similarity threshold must be predetermined. Associated with the self-organizing feature-map-based fuzzy system is a hybrid learning algorithm, which is for initial parameters setting and fine-tuning the parameters of the system.
|
 Additional Information
|
Citation:
Mu-Chun Su, Chee-Yuen Tew,
"A Self-Organizing Feature-Map-Based Fuzzy System,"
ijcnn,
p. 5020,
IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5,
2000
|
