DocumentCode
2319011
Title
Pattern classification using a self-organizing neural network
Author
Pang, Vincent ; Palaniswami, M.
Author_Institution
Dept. of Electr. & Electron. Eng., Melbourne Univ., Vic., Australia
fYear
1990
fDate
24-27 Sep 1990
Firstpage
562
Abstract
A modified self-organizing neural network is presented. The network is based on a laterally inhibited neural network model developed by Kohonen (1988). Preliminary work is focused on the application of the neural model to the classification of feature vectors extracted from texture images. Results obtained from the self-organizing neural classifier are compared with the results of a feedforward neural network trained with the back-propagation algorithm as well as with those of a statistically based classifier
Keywords
learning systems; neural nets; pattern recognition; self-adjusting systems; back-propagation algorithm; feature vectors; feedforward neural network; laterally inhibited neural network; pattern classification; self-organizing neural network; statistically based classifier; texture images; Displays; Feature extraction; Feedforward neural networks; Information technology; Multi-layer neural network; Network topology; Neural networks; Neurofeedback; Neurons; Pattern classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Communication Systems, 1990. IEEE TENCON'90., 1990 IEEE Region 10 Conference on
Print_ISBN
0-87942-556-3
Type
conf
DOI
10.1109/TENCON.1990.152673
Filename
152673
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