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Feature selection using angle modulated simulated Kalman filter for peak classification of EEG signals.

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Title: Feature selection using angle modulated simulated Kalman filter for peak classification of EEG signals.
Authors: Adam A; Applied Control and Robotics (ACR) Laboratory, Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia., Ibrahim Z; Faculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang Malaysia., Mokhtar N; Applied Control and Robotics (ACR) Laboratory, Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia., Shapiai MI; Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia Kuala Lumpur, Jalan Semarak, 54100 Kuala Lumpur, Malaysia., Mubin M; Applied Control and Robotics (ACR) Laboratory, Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia., Saad I; Artificial Intelligence Research Unit (AiRU), Faculty of Engineering, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah Malaysia.
Source: SpringerPlus [Springerplus] 2016 Sep 15; Vol. 5 (1), pp. 1580. Date of Electronic Publication: 2016 Sep 15 (Print Publication: 2016).
Publication Type: Journal Article
Journal Info: Publisher: SpringerPlus Country of Publication: Switzerland NLM ID: 101597967 Publication Model: eCollection Cited Medium: Print ISSN: 2193-1801 (Print) Linking ISSN: 21931801 NLM ISO Abbreviation: Springerplus Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Adam+A%22">Adam A</searchLink>; Applied Control and Robotics (ACR) Laboratory, Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia.<br /><searchLink fieldCode="AU" term="%22Ibrahim+Z%22">Ibrahim Z</searchLink>; Faculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang Malaysia.<br /><searchLink fieldCode="AU" term="%22Mokhtar+N%22">Mokhtar N</searchLink>; Applied Control and Robotics (ACR) Laboratory, Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia.<br /><searchLink fieldCode="AU" term="%22Shapiai+MI%22">Shapiai MI</searchLink>; Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia Kuala Lumpur, Jalan Semarak, 54100 Kuala Lumpur, Malaysia.<br /><searchLink fieldCode="AU" term="%22Mubin+M%22">Mubin M</searchLink>; Applied Control and Robotics (ACR) Laboratory, Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia.<br /><searchLink fieldCode="AU" term="%22Saad+I%22">Saad I</searchLink>; Artificial Intelligence Research Unit (AiRU), Faculty of Engineering, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah Malaysia.
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  Data: <searchLink fieldCode="JN" term="%22101597967%22">SpringerPlus</searchLink> [Springerplus] 2016 Sep 15; Vol. 5 (1), pp. 1580. <i>Date of Electronic Publication: </i>2016 Sep 15 (<i>Print Publication: </i>2016).
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