NEURO-LINGUISTIC APPROACH TO PATTERN-RECOGNITION

被引：1
|
作者：
RAY, KS
GHOSHAL, J
机构：
[1] Electronics and Communication Sciences Unit, Indian Statistical Institute, Calcutta, 700 035, 203, B. T. Road
来源：
FUZZY SETS AND SYSTEMS | 1995年 / 74卷 / 03期
关键词：
APPROXIMATE REASONING; BACKPROPAGATION TYPE NEURAL NETWORK; PATTERN RECOGNITION;
D O I：
10.1016/0165-0114(94)00358-E
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
For pattern recognition, the method of approximate reasoning has been realized through backpropagation type neural network. At the learning stage of the neural network, fuzzy linguistic statements have been used. Once learned, any nonfuzzy and/or fuzzy representation of features can be classified. The performance of the proposed recognition scheme has been compared with that of Bayesian classifier and very satisfactory results have been obtained.
引用
收藏
页码：277 / 305
页数：29
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