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Justification of a Neuron-Adaptive Activation Function
Como, Italy July 24-July 27
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861351IEEE-INNS-ENNS International Joint Co ...
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Shuxiang Xu, Ming Zhang, "Justification of a Neuron-Adaptive Activation Function," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 3, pp. 3465, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3, 2000.
 
 
BibTex
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@article{ 10.1109/IJCNN.2000.861351,
author = {Shuxiang Xu and Ming Zhang},
title = {Justification of a Neuron-Adaptive Activation Function},
journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on},
volume = {3},
year = {2000},
issn = {1098-7576},
pages = {3465},
doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861351},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
TI - Justification of a Neuron-Adaptive Activation Function
SN - 1098-7576
SP
EP
A1 - Shuxiang Xu,
A1 - Ming Zhang,
PY - 2000
VL - 3
JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
ER -
 
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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