کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1713177 | 1013216 | 2007 | 4 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Feature evaluation and extraction based on neural network in analog circuit fault diagnosis*
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Choosing the right characteristic parameter is the key to fault diagnosis in analog circuit. The feature evaluation and extraction methods based on neural network are presented. Parameter evaluation of circuit features is realized by training results from neural network; the superior nonlinear mapping capability is competent for extracting fault features which are normalized and compressed subsequently. The complex classification problem on fault pattern recognition in analog circuit is transferred into feature processing stage by feature extraction based on neural network effectively, which improves the diagnosis effciency. A fault diagnosis illustration validated this method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Systems Engineering and Electronics - Volume 18, Issue 2, 2007, Pages 434-437
Journal: Journal of Systems Engineering and Electronics - Volume 18, Issue 2, 2007, Pages 434-437
نویسندگان
Yuan Haiying, Chen Guangju, Xie Yongle,