On Variable Density Compressive Sampling [PDF]
IEEE Signal Processing Letters, 2011 We advocate an optimization procedure for variable density sampling in the context of compressed sensing. In this perspective, we introduce a minimization problem for the coherence between the sparsity and sensing bases, whose solution provides an optimized sampling profile.
Gilles Puy +2 more
exaly +5 more sources
New Approach Based on Compressive Sampling for Sample Rate Enhancement in DASs for Low-Cost Sensing Nodes [PDF]
Sensors, 2014 The paper deals with the problem of improving the maximum sample rate of analog-to-digital converters (ADCs) included in low cost wireless sensing nodes.
Francesco Bonavolontà +3 more
doaj +4 more sources
Speech Compressive Sampling Using Approximate Message Passing and a Markov Chain Prior [PDF]
Sensors, 2020 By means of compressive sampling (CS), a sparse signal can be efficiently recovered from its far fewer samples than that required by the Nyquist–Shannon sampling theorem.
Xiaoli Jia, Peilin Liu, Sumxin Jiang
doaj +2 more sources
Green Compressive Sampling Reconstruction in IoT Networks [PDF]
Sensors, 2018 In this paper, we address the problem of green Compressed Sensing (CS) reconstruction within Internet of Things (IoT) networks, both in terms of computing architecture and reconstruction algorithms.
Stefania Colonnese +5 more
doaj +2 more sources
Informational Analysis for Compressive Sampling in Radar Imaging [PDF]
Sensors, 2015 Compressive sampling or compressed sensing (CS) works on the assumption of the sparsity or compressibility of the underlying signal, relies on the trans-informational capability of the measurement matrix employed and the resultant measurements, operates ...
Jingxiong Zhang, Ke Yang
doaj +2 more sources
Sparse Signal Representation, Sampling, and Recovery in Compressive Sensing Frameworks
IEEE Access, 2022 Compressive sensing allows the reconstruction of original signals from a much smaller number of samples as compared to the Nyquist sampling rate. The effectiveness of compressive sensing motivated the researchers for its deployment in a variety of ...
Irfan Ahmed +3 more
doaj +3 more sources
Imaging via Compressive Sampling [PDF]
IEEE Signal Processing Magazine, 2008 Image compression algorithms convert high-resolution images into a relatively small bit streams in effect turning a large digital data set into a substantially smaller one. This article introduces compressive sampling and recovery using convex programming.
Justin Romberg
exaly +2 more sources
Compressive sampling based on frequency saliency for remote sensing imaging [PDF]
Scientific Reports, 2017 In saliency-based compressive sampling (CS) for remote sensing image signals, the saliency information of images is used to allocate more sensing resources to salient regions than to non-salient regions.
Jin Li, Zilong Liu, Fengdeng Liu
doaj +2 more sources
Deterministic compressive sampling for high-quality image reconstruction of ultrasound tomography [PDF]
BMC Medical Imaging, 2017 Background A well-known diagnostic imaging modality, termed ultrasound tomography, was quickly developed for the detection of very small tumors whose sizes are smaller than the wavelength of the incident pressure wave without ionizing radiation, compared
Tran Quang Huy +3 more
doaj +2 more sources
Quadrature Compressive Sampling for Multiband Radar Echo Signals
IEEE Access, 2017 In multiband/multifunction radars, the received echoes are usually multiband signals consisting of several subbands with different carrier frequencies. Digital acquisition of the in-phase and quadrature (I and Q) components of each subband is important ...
Shengyao Chen, Feng Xi
doaj +3 more sources