Expanding the Structure Inhibitory Artificial Neural Network Classifiers
Faculty of Computing, Health and Science
School of Engineering and Mathematics
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.