Title :
Use of the Fuzzy Self-Organizing Map in pattern recognition
Author_Institution :
Signal Process. Lab., Tampere Univ. of Technol., Finland
Abstract :
Kohonen´s self-organizing map is one of the best-known neural network models. In previous work, we developed a fuzzy version of the model called: Fuzzy Self-Organizing Map (T. Kohonen, 1988). The new version is similar to the fuzzy logic controllers, and thus it is easy to use and computationally efficient. On the other hand, since the Fuzzy Self-Organizing Map is derived from the original model, the Kohonen learning laws can be used to tune the system. We show how the Fuzzy Self-Organizing Map can be used in pattern recognition. For this purpose, we introduce a new multiple input, multiple output version of the Fuzzy Self-Organizing Map
Keywords :
fuzzy control; fuzzy logic; pattern recognition; self-organising feature maps; Fuzzy Self-Organizing Map; Kohonen learning laws; Kohonen self-organizing map; fuzzy logic controllers; multiple input multiple output version; neural network models; pattern recognition; Books; Fuzzy logic; Fuzzy sets; Intelligent networks; Laboratories; MIMO; Neural networks; Neurons; Pattern recognition; Signal processing;
Conference_Titel :
Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1896-X
DOI :
10.1109/FUZZY.1994.343837
