Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization.
Saved in:
| Title: | Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization. |
|---|---|
| Authors: | Adam A; Applied Control and Robotics (ACR) Laboratory, Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia., Shapiai MI; Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia., Tumari MZ; Faculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia., Mohamad MS; Faculty of Computing, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia., Mubin M; Applied Control and Robotics (ACR) Laboratory, Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia. |
| Source: | TheScientificWorldJournal [ScientificWorldJournal] 2014; Vol. 2014, pp. 973063. Date of Electronic Publication: 2014 Aug 19. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Wiley Country of Publication: United States NLM ID: 101131163 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1537-744X (Electronic) Linking ISSN: 1537744X NLM ISO Abbreviation: ScientificWorldJournal Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 25243236 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization. – Name: Author Label: Authors Group: Au 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="%22Shapiai+MI%22">Shapiai MI</searchLink>; Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia.<br /><searchLink fieldCode="AU" term="%22Tumari+MZ%22">Tumari MZ</searchLink>; Faculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia.<br /><searchLink fieldCode="AU" term="%22Mohamad+MS%22">Mohamad MS</searchLink>; Faculty of Computing, Universiti Teknologi Malaysia, 81310 Johor Bahru, 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. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101131163%22">TheScientificWorldJournal</searchLink> [ScientificWorldJournal] 2014; Vol. 2014, pp. 973063. <i>Date of Electronic Publication: </i>2014 Aug 19. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article; Research Support, Non-U.S. Gov't – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley%22">Wiley </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101131163 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1537-744X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%221537744X%22">1537744X </searchLink><i>NLM ISO Abbreviation: </i>ScientificWorldJournal <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=25243236 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1155/2014/973063 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 973063 Titles: – TitleFull: Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Adam A – PersonEntity: Name: NameFull: Shapiai MI – PersonEntity: Name: NameFull: Tumari MZ – PersonEntity: Name: NameFull: Mohamad MS – PersonEntity: Name: NameFull: Mubin M IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: 2014 Type: published Y: 2014 Identifiers: – Type: issn-electronic Value: 1537-744X Numbering: – Type: volume Value: 2014 Titles: – TitleFull: TheScientificWorldJournal Type: main |
| ResultId | 1 |