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摘要:
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.
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来源 :
ADVANCES IN NEURAL NETWORKS - ISNN 2011, PT I
ISSN: 0302-9743
年份: 2011
卷: 6675
页码: 495-,
语种: 英文
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