A novel spatial architecture artificial neural network based on multilayer feedforward network with mutual inhibition among hidden units

Authors:
Gang Yang;Junfei Qiao;Mingzhe Yuan
Affiliations:
Intelligent Systems Institute, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China;Intelligent Systems Institute, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China;Shenyang Institute of Automation Chinese Academy of Science, Shenyang, China
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
Year:
2011

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Abstract

We propose a Spatial Artificial Neural Network (SANN) with spatial architecture which consists of a multilayer feedforward neural network with hidden units adopt recurrent lateral inhibition connection, all input and hidden neurons have synapses connections with the output neurons. In addition, a supervised learning algorithm based on error back propagation is developed. The proposed network has shown a superior generalization capability in simulations with pattern recognition and non-linear function approximation problems. And, the experimental also shown that SANN has the capability of avoiding local minima problem.