Results 91 to 100 of about 1,448,495 (301)

Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric Inclusion

open access: yesIEEE Access, 2018
Holographic microwave imaging is an innovative method to image biological objects based on their dielectric properties, which has the advantages of high spatial resolution.
Lulu Wang, Mostafa Fatemi
doaj   +1 more source

HomoR-CS: A homogeneous region-based compressed sensing method for SAR tomography

open access: yesInternational Journal of Applied Earth Observation and Geoinformation
The performance of most existing tomographic synthetic aperture radar (SAR) (TomoSAR) methods that reconstruct the scene pixel-by-pixel is degraded by speckle noise and low signal-to-noise ratio. To solve these problems, we propose a homogeneous region-based compressed sensing (HomoR-CS) method for SAR tomography.
Qian Ma 0011   +6 more
openaire   +3 more sources

Compressive Sensing for Inverse Problems

open access: yes, 2018
International audienceThis work is devoted to the presentation of the recent advances of Compressive Sensing (CS) as applied to inverse scattering problems.
Poli, Lorenzo   +13 more
core   +1 more source

Beyond Passivation: Designing Structurally Tailored Artificial Interphases for High‐Energy Lithium‐Based Anodes

open access: yesAdvanced Materials Interfaces, EarlyView.
This review outlines critical engineering design rules for building artificial protective coatings on next‐generation lithium metal and silicon battery anodes. It highlights how balancing structural flexibility with strict electronic and ionic transport limits prevents early battery failure.
Surin Gupte, Vilas G. Pol
wiley   +1 more source

Dual-Layer Compressive Sensing Scheme Incorporating Adaptive Cross Approximation Algorithm for Solving Monostatic Electromagnetic Scattering Problems

open access: yesIEEE Access
The compressive sensing technique can significantly improve the efficiency of the method of moments in solving the monostatic electromagnetic scattering problem by compressing the number of incident sources.
Yalan Gao   +3 more
doaj   +1 more source

Compressive Sensing Ultrasound Beamformed Imaging In Time and Frequency Domain

open access: yes, 2015
High sampling rate is necessary for a quality ultrasound image, which demands expensive data-acquisition and computing devices. Compressive sensing(CS) can reconstruct high quality image with less data.
R Bharath   +7 more
core   +1 more source

A Critical Review on the Evolution of Chitosan‐Based Injectable Hydrogels in Bone Regeneration

open access: yesAdvanced Materials Interfaces, EarlyView.
The graphical illustration depicts hydrogel formulation using chitosan and biocompatible cross‐linkers, major advantages, and incorporation of cells, osteoinductive factors, and therapeutic drugs. Following injection, pH‐responsive gelation enables controlled drug release, promotes cell recruitment and osteogenic differentiation, enhances extracellular
Shivani Santosh Sakhrani   +2 more
wiley   +1 more source

An adaptive approach for integrating primary user behavior in compressive spectrum sensing

open access: yesEURASIP Journal on Wireless Communications and Networking
Compressive 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

Face Recognition Based on Optimized Projections for Distributed Intelligent Monitoring Systems

open access: yesInternational Journal of Distributed Sensor Networks, 2016
Compressive sensing (CS), as a new theory of signal processing, has found many applications. This paper deals with a CS-based face recognition system design.
Aihua Yu   +4 more
doaj   +1 more source

Sparse Recovery Optimization in Wireless Sensor Networks with a Sub-Nyquist Sampling Rate

open access: yesSensors, 2015
Compressive sensing (CS) is a new technology in digital signal processing capable of high-resolution capture of physical signals from few measurements, which promises impressive improvements in the field of wireless sensor networks (WSNs).
Davide Brunelli, Carlo Caione
doaj   +1 more source

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