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| Performance Analysis of Various Activation Functions in Generalized MLP Architectures of Neural Networks
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Source |
International Journal of Artificial Intelligence and Expert Systems (IJAE) |
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Table of Contents |
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Complete Issue PDF(487.48KB) |
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Volume: 1 Issue: 4 |
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Pages: 75-122 |
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Publication
Date: December 2010 |
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ISSN
(Online): 2180-124X |
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Pages |
111 - 122 |
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Author(s) |
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Published
Date |
08-02-2011 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Activation Functions, Multi Layered Perceptron, Neural Networks, Performance Analysis |
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| This Manuscript is indexed in the following databases/websites:- |
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| 1. Docstoc |
| 2. Google Scholar |
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| The activation function used to transform the activation level of a unit (neuron) into an output signal. There are a number of common activation functions in use with artificial neural networks (ANN). The most common choice of activation functions for multi layered perceptron (MLP) is used as transfer functions in research and engineering. Among the reasons for this popularity are its boundedness in the unit interval, the function’s and its derivative’s fast computability, and a number of amenable mathematical properties in the realm of approximation theory. However, considering the huge variety of problem domains MLP is applied in, it is intriguing to suspect that specific problems call for single or a set of specific activation functions. The aim of this study is to analyze the performance of generalized MLP architectures which has back-propagation algorithm using various different activation functions for the neurons of hidden and output layers. For experimental comparisons, Bi-polar sigmoid, Uni-polar sigmoid, Tanh, Conic Section, and Radial Bases Function (RBF) were used. |
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KARAN O?uz, BAYRAKTAR Canan, GÜMÜ?KAYA Haluk, KARLIK Bekir, “Diagnosing Diabetes Using Neural Networks on Small Mobile Devices”, Expert Systems with Applications, vol. 39 (2012), pp. 54-60, 2012 |
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| Bekir Karlik : Colleagues
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| Ahmet Vehbi : Colleagues
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