کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4977732 1451933 2017 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Relevance of polynomial matrix decompositions to broadband blind signal separation
ترجمه فارسی عنوان
نسبت تقسیمات ماتریس چندجملهای به جدایی سیگنال پهنای باند
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
چکیده انگلیسی

The polynomial matrix EVD (PEVD) is an extension of the conventional eigenvalue decomposition (EVD) to polynomial matrices. The purpose of this article is to provide a review of the theoretical foundations of the PEVD and to highlight practical applications in the area of broadband blind source separation (BSS). Based on basic definitions of polynomial matrix terminology such as parahermitian and paraunitary matrices, strong decorrelation and spectral majorisation, the PEVD and its theoretical foundations will be briefly outlined. The paper then focuses on the applicability of the PEVD and broadband subspace techniques - enabled by the diagonalisation and spectral majorisation capabilities of PEVD algorithms - to define broadband BSS solutions that generalise well-known narrowband techniques based on the EVD. This is achieved through the analysis of new results from three exemplar broadband BSS applications - underwater acoustics, radar clutter suppression, and domain-weighted broadband beamforming - and their comparison with classical broadband methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 134, May 2017, Pages 76-86
نویسندگان
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