کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4973947 1451720 2017 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Generalized beta Bayesian compressive sensing model for signal reconstruction
ترجمه فارسی عنوان
مدل سنجش فشرده سازی بتا بنیادی برای بازسازی سیگنال
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
چکیده انگلیسی
A new model-based Bayesian Compressive Sensing (BCS) algorithm is proposed. The statistical structure of the underlying signal is modeled by a two-state signal/noise Hidden Markov Tree (HMT) in the complex wavelet transform domain. This model is based on the recently addressed generalized beta mixtures of Gaussian distribution. A closed-form solution is derived for model parameters via Variational Bayes (VB) inference procedure. Using simulation results, it is shown that the reconstruction error of the proposed algorithm is lower than that of all the related well-known algorithms. Also, its CPU time is in general lower than most investigated algorithms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Digital Signal Processing - Volume 60, January 2017, Pages 163-171
نویسندگان
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