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Volumn , Issue , 2003, Pages 342-348

An optimized artificial neural network approach for epileptiform activity recognition

Author keywords

Artificial neural networks; EEG; Programming tools; Spike detection

Indexed keywords

ALGORITHMS; BRAIN; DECISION MAKING; ELECTROENCEPHALOGRAPHY; NEUROPHYSIOLOGY; OPTIMIZATION; PATIENT MONITORING; PATTERN RECOGNITION;

EID: 1542539009     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (9)
  • 1
    • 0021867672 scopus 로고
    • Methods of Analysis of Nonstationary EEGs, with Emphasis on Segmentation Techniques: A Comparative Review
    • Barlow, J. S., "Methods of Analysis of Nonstationary EEGs, with Emphasis on Segmentation Techniques: A Comparative Review", Journal of Clinical Neurophysiology, 2(3): 267-304, 1985.
    • (1985) Journal of Clinical Neurophysiology , vol.2 , Issue.3 , pp. 267-304
    • Barlow, J.S.1
  • 9
    • 0026675081 scopus 로고
    • Automated Interictal EEG Spike Detection Using Artificial Neural Networks
    • Gabor, A. J., Seyal, M., "Automated Interictal EEG Spike Detection Using Artificial Neural Networks," Electroencephalography and Clinical Neurophysiology, 83: 271-280, 1992.
    • (1992) Electroencephalography and Clinical Neurophysiology , vol.83 , pp. 271-280
    • Gabor, A.J.1    Seyal, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.