M. Sarkar et al., BACKPROPAGATION LEARNING ALGORITHMS FOR CLASSIFICATION WITH FUZZY MEAN-SQUARE ERROR, Pattern recognition letters, 19(1), 1998, pp. 43-51
Most of the real life classification problems have ill defined, imprec
ise or fuzzy class boundaries. Feedforward neural networks with conven
tional backpropagation learning algorithm are not tailored to this kin
d of classification problem. Hence, in this paper, feedforward neural
networks, that use backpropagation learning algorithm with fuzzy objec
tive functions, are investigated. A learning algorithm is proposed tha
t minimizes an error term, which reflects the fuzzy classification fro
m the point of view of possibilistic approach. Since the proposed algo
rithm has possibilistic classification ability, it can encompass diffe
rent backpropagation learning algorithm based on crisp and constrained
fuzzy classification. The efficacy of the proposed scheme is demonstr
ated on a vowel classification problem. (C) 1998 Elsevier Science B.V.