Results 21 to 30 of about 5,109 (308)
Convolutional compressed sensing using deterministic sequences [PDF]
, 2012 This is the author's accepted manuscript (with working title "Semi-universal convolutional compressed sensing using (nearly) perfect sequences"). The final published article is available from the link below. Copyright @ 2012 IEEE.
Cong Ling +4 more
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Compressed sensing applied to modeshapes reconstruction [PDF]
, 2011 Modal analysis classicaly used signals that respect the Shannon/Nyquist theory. Compressive sampling (or Compressed Sampling, CS) is a recent development in digital signal processing that offers the potential of high resolution capture of physical ...
Dimitri Bettebghor +3 more
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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
Sensors, 2019 Devices in a visual sensor network (VSN) are mostly powered by batteries, and in such a network, energy consumption and bandwidth utilization are the most critical issues that need to be taken into consideration. The most suitable solution to such issues
Mansoor Ebrahim +3 more
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Compressive Sensing of Medical Images Based on HSV Color Space
, 2023 Recently, compressive sensing (CS) schemes have been studied as a new compression modality that exploits the sensing matrix in the measurement scheme and the reconstruction scheme to recover the compressed signal.
Gandeva Bayu Satrya +2 more
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CHAOTIC COMPRESSIVE SENSING OF TV –UHF BAND IN IRAQ USING CHEBYSHEV GRAM SCHMIDT SENSING MATRIX
Iraqi Journal of Information & Communication Technology, 2021 Cognitive radio (CR) is a promising technology for solving spectrum sacristy problem. Spectrum sensing is the main step of CR. Sensing the wideband spectrum produces more challenges. Compressive sensing (CS) is a technology used as spectrum sening in
Hadeel S. Abed , Hikmat N. Abdullah
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TamaRISC-CS: An ultra-low-power application-specific processor for compressed sensing [PDF]
2012 IEEE/IFIP 20th International Conference on VLSI and System-on-Chip (VLSI-SoC), 2012 Compressed sensing (CS) is a universal technique for the compression of sparse signals. CS has been widely used in sensing platforms where portable, autonomous devices have to operate for long periods of time with limited energy resources. Therefore, an ultra-low-power (ULP) CS implementation is vital for these kind of energy-limited systems.
Jeremy Constantin +6 more
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Combinatorial Regression and Improved Basis Pursuit for Sparse Estimation [PDF]
, 2012 Sparse representations accurately model many real-world data sets. Some form of sparsity is conceivable in almost every practical application, from image and video processing, to spectral sensing in radar detection, to bio-computation and genomic signal ...
Khajehnejad, M. Amin
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Application of compressive sensing techniques for advanced image processing and digital image transmission [PDF]
Bulletin of Natural Sciences ResearchThe field of compressive sensing (CS) has emerged as a transformative approach in the acquisition and processing of high-dimensional data. This paper presents a comprehensive study on the application of compressive sensing techniques to advanced image ...
Stefanović Nenad +4 more
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Signals, 2022 In this work, we provide a compressive sensing architecture for implementing on a space based observatory for detecting transient photometric parallax caused by gravitational microlensing events.
Asmita Korde-Patel +2 more
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