A comparative stationarity analysis of EEG signals

Author:

Rasoulzadeh V.,Erkus E. C.,Yogurt T. A.,Ulusoy I.,Zergeroğlu S. Aykan

Publisher

Springer Science and Business Media LLC

Subject

Management Science and Operations Research,General Decision Sciences

Reference38 articles.

1. Anisheh, S. M., & Hassanpour, H. (2009). Adaptive segmentation with optimal window length scheme using fractal dimension and wavelet transform. System (Stationarity), 1(4), 5.

2. A.U. BAP. (2012). Developmental dyslexia: Defining the relations between linguistics and EEG data. Ankara University BAP project no: 10B3030001, 2009–2013.

3. Azami, H., Bozorgtabar, B., & Shiroie, M. (2011). Automatic signal segmentation using the fractal dimension and weighted moving average filter. International Journal of Electrical & Computer Sciences, 11(6), 8–15.

4. Azami, H., Saeid, S., & Karim, M. (2011). A novel signal segmentation method based on standard deviation and variable threshold. Journal of Computer Applications, 34(2), 27–34.

5. Azami, H., Karim, M., & Behzad, B. (2012a). An improved signal segmentation using moving average and Savitzky-Golay filter. Journal of Signal and Information Processing, 3(1), 39–44.

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