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