Title :
On the learning rate analysis of a certain class of fuzzy neural network
Author :
Wang, Chi-Hsu ; Liu, Han-Leih
Author_Institution :
Sch. of Microelectron. Eng., Griffith Univ., Brisbane, Qld., Australia
fDate :
6/21/1905 12:00:00 AM
Abstract :
The stable learning rates for a two-layer neural network are discussed first by the Lyapunov stability theorem. This two-layer NN can then be incorporated into a fuzzy neural network (FNN) for a more efficient tuning process by a new genetic algorithm designed in the paper. The main contribution of this methodology is to reduce the searching time by searching only one learning rate in the FNN. All the equations for tuning both the NN and FNN are fully explained
Keywords :
Lyapunov methods; fuzzy neural nets; genetic algorithms; learning (artificial intelligence); multilayer perceptrons; search problems; stability; Lyapunov stability theorem; fuzzy neural network; learning rate analysis; searching time; stable learning rates; tuning process; two-layer neural network; Algorithm design and analysis; Australia; Electronic mail; Fuzzy control; Fuzzy neural networks; Genetic algorithms; Iterative algorithms; Lyapunov method; Microelectronics; Neural networks;
Conference_Titel :
Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
Conference_Location :
Tokyo
Print_ISBN :
0-7803-5731-0
DOI :
10.1109/ICSMC.1999.823244
