Title :
A fuzzy model with exponential partition for approximating SISO nonlinear functions
Author :
Teng, You-Wei ; Wang, Wen-June ; Lee, Pei-Jun
Author_Institution :
Dept. of Electr. Eng., Nat. Central Univ., Chung-li, Taiwan
fDate :
6/23/1905 12:00:00 AM
Abstract :
This paper proposes a fuzzy model with exponential partition to approximate a single input-single output nonlinear function. Given the trajectory of training data will determine the input space partition, rules´ number, and the type of fuzzy sets in antecedent and consequent. An example is given to illustrate the modeling algorithm. It can be seen that the algorithm is simple and efficient for the approximation work
Keywords :
function approximation; fuzzy set theory; fuzzy systems; nonlinear functions; SISO nonlinear function; antecedent; consequent; exponential partition; function approximation; fuzzy model; fuzzy set theory; input space partition; training data; Approximation algorithms; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Inference mechanisms; Information management; Neural networks; Partitioning algorithms; Training data; Turning;
Conference_Titel :
Fuzzy Systems, 2001. The 10th IEEE International Conference on
Conference_Location :
Melbourne, Vic.
Print_ISBN :
0-7803-7293-X
DOI :
10.1109/FUZZ.2001.1008850