The effect of lateral inhibitory connections in spatial architecture neural network

Authors:
Gang Yang;Jun-fei Qiao;Wei Li;Wei Chai
Affiliations:
Intelligent Systems Institute, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, P.R. China;Intelligent Systems Institute, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, P.R. China;Intelligent Systems Institute, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, P.R. China;Intelligent Systems Institute, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, P.R. China
Venue:
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Year:
2013

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Abstract

Based on the theories of lateral inhibition and artificial neural network (ANN), the different lateral inhibitory connections among the hidden neurons of SANN are studied. With the connect mode of activation-inhibition-activation, the SANN will obtain a higher learning accuracy and generalization ability. Furthermore, this inhibitory connection considers both the activation before and after been inhibited by surrounding neurons. The effectiveness of this inhibitory mode is demonstrated by simulation results.