Portal de Periódicos da CAPES

Multilayer perceptron, fuzzy sets, and classification

1992; Institute of Electrical and Electronics Engineers; Volume: 3; Issue: 5 Linguagem: Inglês

10.1109/72.159058

1941-0093

Sankar K. Pal, Sushmita Mitra,

Rough Sets and Fuzzy Logic

A fuzzy neural network model based on the multilayer perceptron, using the backpropagation algorithm, and capable of fuzzy classification of patterns is described. The input vector consists of membership values to linguistic properties while the output vector is defined in terms of fuzzy class membership values. This allows efficient modeling of fuzzy uncertain patterns with appropriate weights being assigned to the backpropagated errors depending upon the membership values at the corresponding outputs. During training, the learning rate is gradually decreased in discrete steps until the network converges to a minimum error solution. The effectiveness of the algorithm is demonstrated on a speech recognition problem. The results are compared with those of the conventional MLP, the Bayes classifier, and other related models. >