Temporal discrete Z-number and its application in assessing EEG signal data of epileptic seizure

Analysis and modeling of a complex physical system, particularly EEG signals involved vague and uncertain information. The approach introduced by Kosanovic using temporal fuzzy set to model a complex system particularly the EEG signal does not address the problem of uncertainty for the time of occur...

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Bibliographic Details
Main Authors: Abdullahi, Mujahid (Author), Tahir Ahmad (Author), Vinod Ramachandran (Author)
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia, 2020-09.
Online Access:Get fulltext
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100 1 0 |a Abdullahi, Mujahid  |e author 
700 1 0 |a Tahir Ahmad,   |e author 
700 1 0 |a Vinod Ramachandran,   |e author 
245 0 0 |a Temporal discrete Z-number and its application in assessing EEG signal data of epileptic seizure 
260 |b Penerbit Universiti Kebangsaan Malaysia,   |c 2020-09. 
856 |z Get fulltext  |u http://journalarticle.ukm.my/15900/1/2.pdf 
520 |a Analysis and modeling of a complex physical system, particularly EEG signals involved vague and uncertain information. The approach introduced by Kosanovic using temporal fuzzy set to model a complex system particularly the EEG signal does not address the problem of uncertainty for the time of occurrence. In this paper, an ordered discrete Z-number is used to construct temporal discrete Z-number to assess EEG signal data of an epileptic seizure for the first time. The proposed temporal discrete Z-number is able to accommodate the problem of uncertainty with regards to the time of occurrence for a given seizure by using and modifying the method for measuring the uncertainty of Z-number. 
546 |a en