ARX System Identification in Biomedical Applications
Aws Zuhair Sameen1, Rosmina Jaafar2, Mohammed Hasan Alwan3
1Aws Zuhair Sameen, Center of Advanced Electronic and Communication Engineering, Faculty of Engineering and Built Environment, University Kebangsaan Malaysia (UKM).
2Rosmina Jaafar, Center of Advanced Electronic and Communication Engineering, Faculty of Engineering and Built Environment, University Kebangsaan Malaysia (UKM).
3Mohammed Hasan Alwan, Department of Communication, Faculty of Electrical and Electronic, University Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia.
Manuscript received on 26 November 2019 | Revised Manuscript received on 14 December 2019 | Manuscript Published on 30 December 2019 | PP: 467-470 | Volume-9 Issue-2S3 December 2019 | Retrieval Number: B11141292S319/2019©BEIESP | DOI: 10.35940/ijitee.B1114.1292S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: System identification approach is a data driven establishing mathematical model of the system that has been widely applied to the astronomy, automatic control, spaceflight, aviation, economics as well as marine ecology and society. At present, system identification has been widely used in the field of biomedical engineering. The status of system identification technique becomes increasingly important with the rapid development of science and technology in various disciplines. This paper is firstly introduced both linear and nonlinear system identification, then briefly explained the Autoregressive Exogenous (ARX) approach, and finally the applications based on ARX system identification in the biomedical engineering field have been presented.
Keywords: System Identification, Autoregressive Exogenous (ARX), Biomedical Engineering, Healthcare, Biomedical Applications.
Scope of the Article: Biomedical Computing