文献
J-GLOBAL ID:201702245762641747
整理番号:17A1386477
非定常信号の改善された分類と解析のための時間-周波数画像特徴集合の性能評価:新生児EEG発作検出への応用【Powered by NICT】
Performance evaluation of time-frequency image feature sets for improved classification and analysis of non-stationary signals: Application to newborn EEG seizure detection
著者 (5件):
Boashash Boualem
(Department of Electrical Engineering, Qatar University, PO Box 2713, Doha, Qatar)
,
Boashash Boualem
(Center for Clinical Research, The University of Queensland, Brisbane, Australia)
,
Barki Hichem
(Department of Electrical Engineering, Qatar University, PO Box 2713, Doha, Qatar)
,
Barki Hichem
(Siemens WLL, Innovation Center, Qatar Science and Technology Park, PO Box 21757, Doha, Qatar)
,
Ouelha Samir
(Department of Electrical Engineering, Qatar University, PO Box 2713, Doha, Qatar)
資料名:
Knowledge-Based Systems
(Knowledge-Based Systems)
巻:
132
ページ:
188-203
発行年:
2017年
JST資料番号:
T0426A
ISSN:
0950-7051
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)