DocumentCode :
3485200
Title :
Self organizing fuzzy neural network: an application to character recognition
Author :
Mishra, Rasmi R.
Author_Institution :
Patni Comput. Syst. Ltd., Mumbai, India
Volume :
5
fYear :
2002
fDate :
18-22 Nov. 2002
Firstpage :
2640
Abstract :
Character recognition is a very important field in DSP. Many different methods are used for this purpose. The ANN technique based on back propagation algorithm is very slow as its computational complexity is very high. On the other hand the Self-orthogonal ANN offers less computational complexity but it is not able to deal with the uncertainty associated with the input data sequence. Hence, fuzzy logic is applied in this case. The fuzzy logic based self-orthogonal neural network has been applied to the scale changed and distorted characters only. The problem of invariance to rotation has been discussed using the four layered feed forward fuzzy neural network.
Keywords :
character recognition; computational complexity; feedforward neural nets; fuzzy neural nets; learning (artificial intelligence); character recognition; computational complexity; four layered feedforward network; fuzzy win-loss status; invariance to rotation; on-line implementation; rapid learning; self organizing fuzzy neural network; Artificial neural networks; Character recognition; Computational complexity; Digital signal processing; Feeds; Fuzzy logic; Fuzzy neural networks; Neural networks; Organizing; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
Type :
conf
DOI :
10.1109/ICONIP.2002.1201974
Filename :
1201974
Link To Document :
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