DocumentCode :
3334218
Title :
Pattern recognition properties of neural networks
Author :
Makhoul, John
Author_Institution :
BBN Syst. & Technol., Cambridge, MA, USA
fYear :
1991
fDate :
30 Sep-1 Oct 1991
Firstpage :
173
Lastpage :
187
Abstract :
Artificial neural networks have been applied largely to solving pattern recognition problems. The authors point out that a firm understanding of the statistical properties of neural nets is important for using them in an effective manner for pattern recognition problems. The author gives an overview of pattern recognition properties for feedforward neural nets, with emphasis on two topics: partitioning of the input space into classes and the estimation of posterior probabilities for each of the classes
Keywords :
feedforward neural nets; pattern recognition; feedforward neural nets; neural networks; pattern recognition; Artificial neural networks; Feedforward neural networks; Humans; Mirrors; Neural networks; Pattern analysis; Pattern recognition; Probability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop
Conference_Location :
Princeton, NJ
Print_ISBN :
0-7803-0118-8
Type :
conf
DOI :
10.1109/NNSP.1991.239524
Filename :
239524
Link To Document :
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