Expanding the Structure Inhibitory Artificial Neural Network Classifiers
Document Type
Conference Proceeding
Publisher
IEEE
Faculty
Faculty of Computing, Health and Science
School
School of Engineering and Mathematics
RAS ID
15
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.
DOI
10.1109/IJCNN.2002.1007601
Comments
Arulampalam, G., & Bouzerdoum, A. (2002). Expanding the structure of shunting inhibitory artificial neural network classifiers. Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on, Honolulu, USA (pp. 2855-2860). Available here