| Full text | |
| Author(s): |
Alyasseri, Zaid Abdi Alkareem
[1, 2]
;
Khader, Ahamad Tajudin
[1]
;
Al-Betar, Mohammed Azmi
[3]
;
Papa, Joao P.
[4]
;
Alomari, Osama Ahmad
[1]
Total Authors: 5
|
| Affiliation: | [1] Univ Sains Malaysia, Sch Comp Sci, George Town 11800 - Malaysia
[2] Univ Kufa, ECE Dept, Fac Engn, Najaf - Iraq
[3] Al Balqa Appl Univ, Dept Informat Technol, Al Huson Univ Coll, Irbid - Jordan
[4] Sao Paulo State Univ, Dept Comp, BR-13084971 Bauru - Brazil
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | IEEE ACCESS; v. 6, p. 76007-76024, 2018. |
| Web of Science Citations: | 4 |
| Abstract | |
In the modern life, the authentication technique for any system is considered as one of the most important and challenging tasks. Therefore, many researchers have developed traditional authentication systems to deal with our digital society. Recently, several studies showed that the brain electrical activity or electroencephalogram (EEG) signals could provide robust and unique features that can be considered as a new biometric authentication technique, given that accurate methods to decompose the signals must also be considered. This paper proposes a novel method for extracting EEG features using multi-objective flower pollination algorithm and the wavelet transform. The proposed method was applied in two scenarios for EEG signal decomposition to extract unique features from the original signals. Moreover, the proposed method is compared with the state-of-the-art techniques using different criteria with promising results. (AU) | |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 16/19403-6 - Energy-based learning models and their applications |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Regular Research Grants |