Modified neural network activation function
Neural Network is said to emulate the brain, though, its processing is not quite how the biological brain really works. The Neural Network has witnessed significant improvement since 1943 to date. However, modifications on the Neural Network mainly focus on the structure itself, not the activat...
| Main Authors: | , , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/39658/ http://irep.iium.edu.my/39658/ http://irep.iium.edu.my/39658/1/39658.pdf http://irep.iium.edu.my/39658/4/39658_Modified%20Neural%20Network%20Activation%20Function.SCOPUS.pdf |
| Summary: | Neural Network is said to emulate the brain,
though, its processing is not quite how the biological brain
really works. The Neural Network has witnessed significant
improvement since 1943 to date. However, modifications on the
Neural Network mainly focus on the structure itself, not the
activation function despite the critical role of activation
function in the performance of the Neural Network. In this
paper, we present the modification of Neural Network
activation function to improve the performance of the Neural
Network. The theoretical background of the modification,
including mathematical proof is fully described in the paper.
The modified activation function is code name as SigHyper.
The performance of SigHyper was evaluated against state of
the art activation function on the crude oil price dataset.
Results suggested that the proposed SigHyper was found to
improved accuracy of the Neural Network. Analysis of
variance showed that the accuracy of the SigHyper is
significant. It was established that the SigHyper require further
improvement. The activation function proposed in this
research has added to the activation functions already
discussed in the literature. The study may motivate researchers
to further modify activation functions, hence, improve the
performance of the Neural Network. |
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