DocumentCode
2135652
Title
Stability analysis of neural networks using stability conditions of fuzzy systems
Author
Tanaka, Kazuo ; Sano, Manabu
Author_Institution
Dept. of Mech. Syst. Eng., Kanazawa Univ., Japan
fYear
1993
fDate
1993
Firstpage
422
Abstract
The authors discuss stability of neural networks using stability conditions of fuzzy systems. A parameter region (PR) representation, which graphically shows the location of fuzzy if-then rules in consequent parameter space, is proposed, using the concepts of edge rule (matrix) and minimum representation. The stability criterion of neural networks is illustrated in terms of the PR representation. Some properties for stability of neural networks are derived from the results on the stability criterion
Keywords
fuzzy logic; neural nets; stability criteria; edge rule; fuzzy if-then rules; fuzzy systems; minimum representation; neural networks; parameter region representation; stability criterion; Fuzzy sets; Fuzzy systems; Input variables; Mechanical systems; Neural networks; Nonlinear systems; Stability analysis; Stability criteria; Sufficient conditions; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 1993., Second IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-0614-7
Type
conf
DOI
10.1109/FUZZY.1993.327425
Filename
327425
Link To Document