Results 71 to 80 of about 3,276,837 (200)
Incorporating Primary Occupancy Patterns in Compressive Spectrum Sensing
IEEE Access, 2019 Wideband spectrum sensing remains one of the challenging problems facing the wide deployment of cognitive radio networks. Compressive sensing (CS) was proposed as a promising approach to this problem by utilizing the sparse structure of the underutilized
Omar M. Eltabie +2 more
doaj +1 more source
A Systematic Review of Compressive Sensing: Concepts, Implementations and Applications
IEEE Access, 2018 Compressive Sensing (CS) is a new sensing modality, which compresses the signal being acquired at the time of sensing. Signals can have sparse or compressible representation either in original domain or in some transform domain.
M. Rani, S. B. Dhok, R. Deshmukh
semanticscholar +1 more source
Model-based Optimization of Compressive Antennas for High-Sensing-Capacity Applications [PDF]
, 2015 This paper presents a novel, model-based compressive antenna design method for high sensing capacity imaging applications. Given a set of design constraints, the method maximizes the sensing capacity of the compressive antenna by varying the constitutive
Martinez-Lorenzo, Jose Angel +1 more
core
An adaptive approach for integrating primary user behavior in compressive spectrum sensing
EURASIP Journal on Wireless Communications and NetworkingCompressive sensing (CS) has been widely used to sense the wideband spectrum with fewer measurements by taking advantage of radio spectrum underutilization.
Ahmed A. Tawfik +2 more
doaj +1 more source
Sparse Representation for Wireless Communications: A Compressive Sensing Approach [PDF]
IEEE Signal Processing Magazine, 2018 Sparse representation can efficiently model signals in different applications to facilitate processing. In this article, we will discuss various applications of sparse representation in wireless communications, with a focus on the most recent compressive
Zhijin Qin +4 more
semanticscholar +1 more source
A Review of Sparse Recovery Algorithms
IEEE Access, 2019 Nowadays, a large amount of information has to be transmitted or processed. This implies high-power processing, large memory density, and increased energy consumption.
Elaine Crespo Marques +4 more
doaj +1 more source
Nonconvex compressive video sensing [PDF]
Journal of Electronic Imaging, 2016 High-speed cameras explore more details than normal cameras in the time sequence, while the conventional video sampling suffers from the trade-off between temporal and spatial resolutions due to the sensor's physical limitation. Compressive sensing overcomes this obstacle by combining the sampling and compression procedures together.
Liangliang, Chen +7 more
openaire +2 more sources
, 2013 This work considers an estimation task in compressive sensing, where the goal is to estimate an unknown signal from compressive measurements that are corrupted by additive pre-measurement noise (interference, or clutter) as well as post-measurement noise,
Haupt, Jarvis +2 more
core +1 more source
Compressive Super-Resolution Imaging Based on Scrambled Block Hadamard Ensemble
IEEE Photonics Journal, 2016 Recent advances in the field of compressive sensing indicate that it is possible to robustly reconstruct images from judicious compressive samples.
Yicheng Sun +4 more
doaj +1 more source
An Energy-Efficient Compressive Sensing-Based Clustering Routing Protocol for WSNs
IEEE Sensors Journal, 2019 A novel algorithm which combined the merits of the clustering strategy and the compressive sensing-based (CS-based) scheme was proposed in this paper.
Quan Wang +3 more
semanticscholar +1 more source