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Volumn , Issue , 2012, Pages 98-101

Classification of normal and epileptic EEG signal using time amp; Frequency domain features through artificial neural network

Author keywords

Artificial Neural Network; Electroencephalogram (EEG); Epilepsy; Feedforward network; seizure detection

Indexed keywords

BRAIN DISORDERS; BROAD SPECTRUM; DATA SETS; DETECTION SYSTEM; EEG SIGNALS; EPILEPSY; EPILEPTIC EEG; EPILEPTIC SPIKES; FEED-FORWARD ARTIFICIAL NEURAL NETWORKS; FEED-FORWARD NETWORK; FREQUENCY DOMAINS; GERMANY; NEURONAL ACTIVITIES; SEIZURE DETECTION; SELF ADAPTATION; SINGLE CHANNELS; SLIDING WINDOW TECHNIQUES; TRANSIENT DISTURBANCES;

EID: 84867966842     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICACC.2012.21     Document Type: Conference Paper
Times cited : (34)

References (7)
  • 1
    • 0020382517 scopus 로고
    • Automatic recognition of epileptic seizures in the EEG
    • DOI 10.1016/0013-4694(82)90038-4
    • Gotman, J, "Automatic recognition of epileptic seizure in the EEG", Electroencephalograph and Clinical Neurophysiology, 54, 530-540, 1982. (Pubitemid 13244246)
    • (1982) Electroencephalography and Clinical Neurophysiology , vol.54 , Issue.5 , pp. 530-540
    • Gotman, J.1
  • 4
    • 84867978646 scopus 로고    scopus 로고
    • http://epileptologie-bonn.de/cms/front-content.php?idcat=193&lang= 3&changelang=3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.