کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6957203 | 1451915 | 2018 | 38 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Adaptive step-size iterative algorithm for sparse signal recovery
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
We develop an efficient algorithm, which can adaptively infer the step-size in each iteration, to recover sparse signal from compressive measurements. This algorithm is formulated as an iteratively alternating projection strategy; the first step projects the measurements/residuals to the signal space, implemented via a Bayesian model, and the second step projects the results obtained in the first step to the â1-ball. Variational Bayesian (VB) is employed to perform the inference of the Bayesian model and Euclidean projection (EP) is utilized to impose sparsity; thus our algorithm is dubbed VB-EP. We further derive a maximum likelihood estimator (MLE) of the Bayesian model to speed up the inference with a pre-determined step size. The convergence of this MLE-EP algorithm is analyzed and compared with the iterative shrinkage/thresholding algorithm based on the restricted isometry property of the compressive sensing matrix. Simulation results verify the superior performance of the proposed algorithm.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 152, November 2018, Pages 273-285
Journal: Signal Processing - Volume 152, November 2018, Pages 273-285
نویسندگان
Xin Yuan,