DocumentCode :
1713829
Title :
Neural Network Rule Extraction and the LED Display Recognition Problem
Author :
Setiono, Rudy ; Tanaka, Masahiro
Author_Institution :
Sch. of Comput., Nat. Univ. of Singapore, Singapore, Singapore
Volume :
2
fYear :
2010
Firstpage :
53
Lastpage :
56
Abstract :
This paper presents the results from a neural network rule extraction algorithm applied to the LED display recognition problem. We show that pruned neural networks with small number of hidden nodes and connections are able to recognize all the 10 digits from 0 to 9. Earlier work by other researchers demonstrated how symbolic fuzzy rules can be extracted from trained neural networks to solve this problem. Our rules in contrast are crisp rules, and they are obtained from smaller networks. As a result, simpler and easier to understand rules are obtained. These rules give us an insight of how neural networks differentiate one digit from the rest in LED display recognition problem.
Keywords :
LED displays; fuzzy neural nets; LED display recognition; neural network rule extraction; symbolic fuzzy rules; Accuracy; Artificial neural networks; Data mining; Light emitting diodes; Machine learning algorithms; Noise; Training; LED display recognition; pruning; rule extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2010 22nd IEEE International Conference on
Conference_Location :
Arras
ISSN :
1082-3409
Print_ISBN :
978-1-4244-8817-9
Type :
conf
DOI :
10.1109/ICTAI.2010.83
Filename :
5671432
Link To Document :
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