Advanced fuzzy set: an application to flat electroencephalography image

Suzelawati Zenian, and Tahir Ahmad, and Amidora Idris, (2020) Advanced fuzzy set: an application to flat electroencephalography image. In: Computational Science and Technology.

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Epileptic seizures refer to temporary disturbance in the electrical activity of the brain. The real time electrical activities of the cortical and subcortical neuronal activity are recorded by using Electroencephalogram (EEG) whereby few specific electrodes are placed on the scalp. EEG measures the differential voltage fluctuations resulting from ionic current flows within the neurons of the brain and can detect the changes over milliseconds. In this study, the image form of the EEG signals known as Flat EEG image is carried out. The advanced fuzzy techniques namely intuitionistic fuzzy set (IFS) and type-2 fuzzy set are explored to enhance the image of Flat EEG. The parameter in intuitionistic fuzzy image is optimized using intuitionistic fuzzy entropy. Whereas Hamacher t-conorm is applied for type-2 fuzzy enhancement. Experimental results on Flat EEG input images at two different time show that type-2 produced better output images compared to intuitionistic fuzzy methods.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: Flat EEG , intuitionistic fuzzy set , type-2 fuzzy set , uncertainty , image enhancement
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: FACULTY > Faculty of Science and Natural Resources
Depositing User: Noraini
Date Deposited: 01 Jul 2020 03:46
Last Modified: 01 Jul 2020 03:46

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