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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3
Justification of a Neuron-Adaptive Activation Function
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
Shuxiang Xu, University of Tasmania
Ming Zhang, University of Western Sydney Macarthur
An empirical justification of a neuron-adaptive activation function for feed-forward neural networks has been proposed in this paper. Simulation results reveal that feed-forward neural networks with the proposed neuron-adaptive activation function present several advantages over traditional neuron-fixed feed-forward networks such as increased flexibility, much reduced network size, faster learning, and lessened approximation errors.
Citation:
Shuxiang Xu, Ming Zhang, "Justification of a Neuron-Adaptive Activation Function," ijcnn, vol. 3, pp.3465, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3, 2000
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