Classification of EEG Signals Using Spiking Neural Networks

被引：0

作者：

Tahtirvanci, Aykut ^{[1
]}

Durdu, Akif ^{[1
]}

Yilmaz, Burak ^{[2
]}

机构：

[1] Selcuk Univ, Elekt Elekt Muhendisligi, Konya, Turkey

[2] Konya Gida & Tarim Univ, Elekt Elekt Muhendisligi, Konya, Turkey

来源：

2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2018年

关键词：

spiking neural networks; EEG; artifical neural networks; Izhikevich neuron model;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In signal processing applications of conventional artificial neural networks, the processing time of the data is high and the accuracy rates are not good enough. At the same time, time-dependent processing is not possible. In this study, classification of EEG signals was performed using an artificial neural network including the characteristics of spiking neural networks. Successful results were obtained using large data sets. Moreover, by using the neuron model of Eugene M. Izhikevich as the spiking neural network model, the EEG signals were processed biologically realistically.

引用

页数：4

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