کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6951928 1451722 2016 43 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
First- and second-order cyclostationary signal separation using morphological component analysis
ترجمه فارسی عنوان
تجزیه و تحلیل سیگنالسیون ایستگاه اول و دوم با استفاده از تجزیه و تحلیل مؤلفه های مورفولوژیکی
کلمات کلیدی
چرخه اعتبار تجزیه و تحلیل جزء مورفولوژیکی، جداسازی سیگنال تعیین کننده / تصادفی تفکیک منبع، تجزیه و تحلیل سیگنال بیومکانیک،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
چکیده انگلیسی
The objective of this research paper is to exploit the CS characteristics of signals in the context of morphological component analysis (MCA) method. It proposes a novel methodology used for separating between the periodic (First-Order Cyclostationarity: CS1) and random (Second-Order Cyclostationarity: CS2) sources by means of one sensor measurement. This MCACS2 methodology is based on MCA, where each of the two sources is sparsely represented by a special dictionary: i) the CS1 periodic structure is sparsely represented by means of the Discrete Cosine Transform dictionary, and ii) the CS2 random component is sparsely represented by a new proposed dictionary derived from Envelope Spectrum Analysis. Subsequently, a simulation study is performed in order to validate the proposed new MCACS2 method followed by tests on real GRF biomechanical signals. The result concludes by stating that such a novel algorithm provides an additional way for the exploitation of cyclostationarity and may be useful in other domain applications.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Digital Signal Processing - Volume 58, November 2016, Pages 134-144
نویسندگان
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