TY - GEN
T1 - Comparison of two on-line hybrid system identification methods
AU - Alizadeh, T.
AU - Alizadeh, A.
AU - Sepasi, S.
AU - Barzegary, S.
PY - 2010
Y1 - 2010
N2 - In this paper we compare two recently proposed algorithms for online identification of hybrid systems. We consider the adaptive growing and pruning Radial Basis Function (RBF) neural network based and the potential fuzzy clustering based procedures. Specific behaviors of the procedures are pointed out, using a well known two dimensional example.
AB - In this paper we compare two recently proposed algorithms for online identification of hybrid systems. We consider the adaptive growing and pruning Radial Basis Function (RBF) neural network based and the potential fuzzy clustering based procedures. Specific behaviors of the procedures are pointed out, using a well known two dimensional example.
KW - Hybrid systems - identification - GAPRBF neural network - potential Fuzzy Clustering
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M3 - Conference contribution
AN - SCOPUS:79952414441
SN - 9789881701282
T3 - Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010
SP - 1020
EP - 1023
BT - Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010
T2 - International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010
Y2 - 17 March 2010 through 19 March 2010
ER -