Analysis of EEG Signals by Emprical Mode Decomposition and Mutual Information

被引：0

作者：

Mert, Ahmet ^{[1
]}

Akan, Aydin ^{[2
]}

机构：

[1] Piri Reis Univ, Gemi Makinalari Isletme Muhendisligi Bolumu, Istanbul, Turkey

[2] Istanbul Univ, Elekt Elekt Muhendisligi Bolumu, Istanbul, Turkey

来源：

2013 21ST SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2013年

关键词：

Empirical mode decomposition; epileptic EEG analysis; mutual information;

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：

Empirical mode decomposition has been recently proposed to analyze non-stationary signals. It decomposes the signal into intrinsic mode functions (IMF) which are derived from the signal itself. However, it is still an unknown issue which IMF involves more information of the signal. In this study, single channel EEG signals from normal and epileptic recordings are analyzed. Hence, mutual information is computed between the autocorrelation function (ACF) of a reference and a given EEG's first IMF. The proposed method is applied to two different datasets to show its classification capability of normal and epileptic EEG signals.

引用

页数：4

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