کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
531721 | 869870 | 2007 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Atrial fibrillation classification with artificial neural networks
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
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چکیده انگلیسی
The acquired 72 normal sinus rhythm ECGs and 80 ECGs with atrial fibrillation (AF) are decomposed with ‘db10’ Daebauchies wavelets at level 6 and power spectral density was calculated for each decomposed signal with Welch method. Average power spectral density was calculated for six subbands and normalized to be used as input to the neural network. Levenberg–Marquart backpropagation feed forward neural network was built from logarithmic sigmoid transfer functions in three-layer form. The trained network was tested on 24 normal and 28 AF state ECGs. The classification performance was accomplished as 100% accurate.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 40, Issue 11, November 2007, Pages 2967–2973
Journal: Pattern Recognition - Volume 40, Issue 11, November 2007, Pages 2967–2973
نویسندگان
Sadik Kara, Mustafa Okandan,