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Modeling brain wave data by using artificial neural networks

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

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Modeling brain wave data by using artificial neural networks. / Aladag, Cagdas Hakan; Egrioglu, Erol; Kadilar, Cem.
In: Hacettepe Journal of Mathematics and Statistics, Vol. 39, No. 1, 23.04.2010, p. 81-88.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Aladag, CH, Egrioglu, E & Kadilar, C 2010, 'Modeling brain wave data by using artificial neural networks', Hacettepe Journal of Mathematics and Statistics, vol. 39, no. 1, pp. 81-88.

APA

Aladag, C. H., Egrioglu, E., & Kadilar, C. (2010). Modeling brain wave data by using artificial neural networks. Hacettepe Journal of Mathematics and Statistics, 39(1), 81-88.

Vancouver

Aladag CH, Egrioglu E, Kadilar C. Modeling brain wave data by using artificial neural networks. Hacettepe Journal of Mathematics and Statistics. 2010 Apr 23;39(1):81-88.

Author

Aladag, Cagdas Hakan ; Egrioglu, Erol ; Kadilar, Cem. / Modeling brain wave data by using artificial neural networks. In: Hacettepe Journal of Mathematics and Statistics. 2010 ; Vol. 39, No. 1. pp. 81-88.

Bibtex

@article{c31b4925d4cc4b6bbf13d35cd99a3461,
title = "Modeling brain wave data by using artificial neural networks",
abstract = "Artificial neural networks can successfully model time series in real life. Because of their success, they have been widely used in various fields of application. In this paper, artificial neural networks are used to model brain wave data which has been recorded during the Wisconsin Card Sorting Test. The forecasting performances of different artificial neural network models, such as feed forward and recurrent neural networks, using both linear and nonlinear activation functions in the output neuron, are examined. As a result of the analysis, it is found that artificial neural networks model the data successfully and all the models employed produce very accurate forecasts.",
keywords = "Activation function, Brain wave data, Elman recurrent neural networks, Feed forward neural networks, Forecasting, Wisconsin card sorting test",
author = "Aladag, {Cagdas Hakan} and Erol Egrioglu and Cem Kadilar",
year = "2010",
month = apr,
day = "23",
language = "English",
volume = "39",
pages = "81--88",
journal = "Hacettepe Journal of Mathematics and Statistics",
issn = "1303-5010",
publisher = "Hacettepe University",
number = "1",

}

RIS

TY - JOUR

T1 - Modeling brain wave data by using artificial neural networks

AU - Aladag, Cagdas Hakan

AU - Egrioglu, Erol

AU - Kadilar, Cem

PY - 2010/4/23

Y1 - 2010/4/23

N2 - Artificial neural networks can successfully model time series in real life. Because of their success, they have been widely used in various fields of application. In this paper, artificial neural networks are used to model brain wave data which has been recorded during the Wisconsin Card Sorting Test. The forecasting performances of different artificial neural network models, such as feed forward and recurrent neural networks, using both linear and nonlinear activation functions in the output neuron, are examined. As a result of the analysis, it is found that artificial neural networks model the data successfully and all the models employed produce very accurate forecasts.

AB - Artificial neural networks can successfully model time series in real life. Because of their success, they have been widely used in various fields of application. In this paper, artificial neural networks are used to model brain wave data which has been recorded during the Wisconsin Card Sorting Test. The forecasting performances of different artificial neural network models, such as feed forward and recurrent neural networks, using both linear and nonlinear activation functions in the output neuron, are examined. As a result of the analysis, it is found that artificial neural networks model the data successfully and all the models employed produce very accurate forecasts.

KW - Activation function

KW - Brain wave data

KW - Elman recurrent neural networks

KW - Feed forward neural networks

KW - Forecasting

KW - Wisconsin card sorting test

M3 - Journal article

AN - SCOPUS:77951090057

VL - 39

SP - 81

EP - 88

JO - Hacettepe Journal of Mathematics and Statistics

JF - Hacettepe Journal of Mathematics and Statistics

SN - 1303-5010

IS - 1

ER -