Results 31 to 40 of about 2,616,250 (281)
A Compressed Sensing Framework for Magnetic Resonance Fingerprinting [PDF]
, 2014 Inspired by the recently proposed magnetic resonance fingerprinting (MRF) technique, we develop a principled compressed sensing framework for quantitative MRI. The three key components are a random pulse excitation sequence following the MRF technique, a
Wiaux, Yves; id_orcid +5 more
core +1 more source
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
core +1 more source
Compressed quantitative MRI: Bloch response recovery through iterated projection [PDF]
, 2014 Inspired by the recently proposed Magnetic Resonance Fingerprinting technique, we develop a principled compressed sensing framework for quantitative MRI.
Wiaux, Yves; id_orcid +8 more
core +1 more source
PURIFY: a new algorithmic framework for next-generation radio-interferometric imaging [PDF]
, 2014 In recent works, compressed sensing (CS) and convex opti- mization techniques have been applied to radio-interferometric imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. We review our latest con- tributions [1,
Wiaux, Yves; id_orcid +8 more
core +2 more sources
Distributed Compressive Sensing: A Deep Learning Approach [PDF]
IEEE Transactions on Signal Processing, 2016 Various studies that address the compressed sensing problem with Multiple Measurement Vectors (MMVs) have been recently carried. These studies assume the vectors of the different channels to be jointly sparse. In this paper, we relax this condition. Instead we assume that these sparse vectors depend on each other but that this dependency is unknown. We
Hamid Palangi +2 more
openaire +2 more sources
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
core +1 more source
The direction of arrival estimation method based on gridless compressed sensing
上海师范大学学报. 自然科学版, 2020 Efficient direction of arrival(DOA) estimation for densely distributed targets was a difficult and hot spot in current high-precision positioning technology.There were many problems and issuesfor existing DOA estimation methods which were designed based ...
GU Xu, WEI Shuang, LI Li, SU Ying
doaj +1 more source
, 2022 Il compressed sensing è una tecnica di risoluzione di un sistema indeterminato di equazioni lineari sotto le ipotesi che la soluzione del sistema sia S-sparsa, ovvero che in un'opportuna rappresentazione abbia al più S elementi non nulli.
Celin, Alberto
core
Compressed Sensing and Fluorescence Microscopy [PDF]
, 2022 La mia tesina tratta della tecnica di acquisizione dati del compressed sensing e di una sua applicazione nel microscopio a fluorescenza. Attraverso questa tecnica è infatti possibile acquisire direttamente la versione compressa del segnale, ignorando in
Bizzotto, Chiara
core
Distributed Compressed Video Sensing in Camera Sensor Networks
International Journal of Distributed Sensor Networks, 2012 With the booming of video devices ranging from low-power visual sensors to mobile phones, the video sequences captured by these simple devices must be compressed easily and reconstructed by relatively more powerful servers. In such scenarios, distributed
Yu Liu, Xuqi Zhu, Lin Zhang, Sung Ho Cho
doaj +1 more source