1D-local binary pattern based feature extraction for classification of epileptic EEG signals

DOI10.1016/J.AMC.2014.05.128zbMath1335.92049OpenAlexW1970917709MaRDI QIDQ279886

Yılmaz Kaya, Ramazan Tekin, Selçuk Yıldırım, Murat Uyar

Publication date: 29 April 2016

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2014.05.128

zbMATH Keywords

feature extractionepilepsy1D-local binary patternsEEG classification

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55)

Related Items (2)

A new similarity index for nonlinear signal analysis based on local extrema patterns ⋮ Automated Identification of Epileptic Seizures from EEG Signals Using FBSE-EWT Method

Cites Work

• Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform
• Implementing eigenvector methods/probabilistic neural networks for analysis of EEG signals
• Unnamed Item

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