Title :
Fuzzy systems as universal approximators
Author_Institution :
Dept. of Electr. Eng.-Syst., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
The author shows that an additive fuzzy system can approximate any continuous function on a compact domain to any degree of accuracy. Fuzzy systems are dense in the space of continuous functions. The fuzzy system approximates the function by covering its graph with fuzzy patches in the input-output state space. Each fuzzy rule defines a fuzzy patch and connects commonsense knowledge with state-space geometry. Neural or statistical clustering algorithms can approximate the unknown fuzzy patches and generate fuzzy systems from training data
Keywords :
fuzzy set theory; modelling; state-space methods; additive fuzzy system; commonsense knowledge; compact domain; continuous function; dense systems; fuzzy patches; input-output state space; neural clustering algorithms; state-space geometry; statistical clustering algorithms; universal approximators; Approximation algorithms; Clustering algorithms; Fuzzy sets; Fuzzy systems; Geometry; Hypercubes; Image processing; Signal processing; State-space methods; Training data;
Conference_Titel :
Fuzzy Systems, 1992., IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0236-2
DOI :
10.1109/FUZZY.1992.258720
