DocumentCode
1681365
Title
Expanding the structure of shunting inhibitory artificial neural network classifiers
Author
Arulampalam, Ganesh ; Bouzerdoum, Abdesselam
Author_Institution
Edith Cowan Univ., Joondalup, WA, Australia
Volume
3
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
2855
Lastpage
2860
Abstract
Shunting inhibitory artificial neural networks (SIANNs) are biologically inspired networks in which the neurons interact via a nonlinear mechanism called shunting inhibition. They are capable of producing complex, nonlinear decision boundaries. The structure and operation of feedforward SIANNs and some enhancements are presented. They are applied to several classification problems, and their performance is compared to that of the multilayer perceptron classifier
Keywords
feedforward neural nets; pattern classification; biologically inspired networks; complex nonlinear decision boundaries; feedforward SIANN; shunting inhibitory artificial neural network classifier structure expansion; Adaptive control; Artificial neural networks; Australia; Cellular neural networks; Differential equations; Gain control; Image processing; Multilayer perceptrons; Neurons; Programmable control;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1007601
Filename
1007601
Link To Document