کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1713150 | 1013216 | 2007 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Digital modulation classification using multi-layer perceptron and time-frequency features
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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
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چکیده انگلیسی
Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributions are introduced for the modulation classification of communication signals. The extracted time-frequency features have good classification information, and they are insensitive to signal to noise ratio (SNR) variation. According to good classification by the correct rate of a neural network classifier, a multilayer perceptron (MLP) classifier with better generalization, as well as, addition of time-frequency features set for classifying six difierent modulation types has been proposed. Computer simulations show that the MLP classifier outperforms the decision-theoretic classifier at low SNRs, and the classification experiments for real MPSK signals verify engineering significance of the MLP classifier.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Systems Engineering and Electronics - Volume 18, Issue 2, 2007, Pages 249-254
Journal: Journal of Systems Engineering and Electronics - Volume 18, Issue 2, 2007, Pages 249-254
نویسندگان
Yuan Ye, Mei Wenbo,