Aug 16, 2012 · The theory of Bayesian compressive sensing is briefly introduced and the differential entropy for recovery signal is deduced.
Numerical simulations on random step signal and real radar signal and 2D image verify that the proposed adaptive sampling algorithm has good performance. This ...
Bibliographic details on Adaptive sampling with Bayesian compressive sensing in radar sensor networks and image.
Jan 27, 2017 · In order to improve speed and efficiency over traditional scanning methods, a Bayesian compressive sensing algorithm using adaptive spatial ...
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Adaptive sampling with Bayesian compressive sensing in radar sensor networks and image. EURASIP Journal on Wireless Communications and Networking, Vol. 2012 ...
In this paper, a novel adaptive rate allocation block CS scheme for images based on a hybrid sparsity estimation model is proposed.
Compressed Sensing Radar Imaging: Fundamentals, Challenges, and ...
www.ncbi.nlm.nih.gov › PMC6679252
Jul 13, 2019 · The methods presented in this paper include the minimum variance unbiased estimation, least squares (LS) estimation, Bayesian maximum a ...
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Mar 24, 2015 · Compressive sampling or compressed sensing (CS) works on the assumption of the sparsity or compressibility of the underlying signal, ...
Compressive sensing (CS) techniques offer a framework for the detection and allocation of sparse signals with a reduced number of samples.
Compressive sensing (CS) applied to through-the-wall radar imaging (TWRI) exploits the group sparsity of a target scene in the presence of wall clutter and ...