Title :
A fuzzy-ART-enhanced neural classifier
Author :
Chou, J.S. ; Ho, C.S.
Author_Institution :
Dept. of Electron. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
Abstract :
A neural network classifier enhanced by the fast-learning fuzzy ART mechanism is presented. The learning algorithm combines the fuzzy ART procedure for structure learning and the error backpropagation learning scheme for parameter learning. The former helps self-generate a proper hidden layer and auto-initialize the connection weights of related layers to alleviate the local minima problem and to improve the learning speed. The experiments show that the proposed model can exhibit high-quality classification capability in either a continuous, discrete, linear or a nonlinear domain
Keywords :
ART neural nets; backpropagation; fuzzy neural nets; fuzzy systems; error backpropagation learning scheme; fuzzy-ART-enhanced neural classifier; high-quality classification capability; learning algorithm; local minima problem; neural network classifier; parameter learning; structure learning; Artificial neural networks; Computer errors; Computer networks; Convergence; Equations; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Intelligent systems; Subspace constraints;
Conference_Titel :
Knowledge-Based Intelligent Information Engineering Systems, 1999. Third International Conference
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-5578-4
DOI :
10.1109/KES.1999.820229