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http://www.ece.iastate.edu/~namrata/modcs_preprint.pdf
Modified-CS: Modifying Compressive Sensing for Problems with Partially Known Support Namrata Vaswani and Wei Lu ECE Dept., Iowa State University, Ames, IA 50011, USA, Email: [email protected] Abstract—We study the problem of reconstructing a sparse signal from a limited number of its linear projections when a part of its support is known.
https://arxiv.org/pdf/0903.5066.pdf
Problems with Partially Known Support Namrata Vaswani and Wei Lu Abstract—We study the problem of reconstructing a sparse signal from a limited number of its linear projections when a part of its support is known, although the known part may contain some errors. The “known” part of the support, denoted T, may be available from prior ...
https://www.sciencedirect.com/science/article/pii/S0165168412002411
We study recovering sparse and compressible signals using l p minimization with p < 1 when some part of the support of the signal is known a priori. Sparse reconstruction method based on l p minimization with partially known set is proposed and recovery conditions are given. Theoretical results show that l p minimization with partially known support is stable and robust.Cited by: 24
https://ieeexplore.ieee.org/document/7574795/
Under the assumption that the signal of interest, with some known locations of the nonzero coefficients, has a sparse representation under some redundant dictionaries, we modify the Signal Space CoSaMP algorithm by incorporating the partially known support into the recovery process.Author: Shiying He, Yao Wang, Jianjun Wang
https://ieeexplore.ieee.org/document/8531673/
Nov 12, 2018 · Joint Sparsity With Partially Known Support and Application to Ultrasound Imaging Abstract: We investigate the benefits of known partial support for the recovery of joint-sparse signals and demonstrate that it is advantageous in terms of recovery performance for both rank-blind and rank-aware algorithms. We suggest extensions of several joint ...Author: Adrien Besson, Dimitris Perdios, Yves Wiaux, Jean-Philippe Thiran
https://www.researchgate.net/publication/220736174_Iterative_algorithm_for_compressed_sensing_with_partially_know_support
Recent works in modified compressed sensing (CS) show that reconstruction of sparse or compressible signals with partially known support yields better results than traditional CS.
https://www.researchgate.net/publication/49626901_Compressed-Sensing_Dynamic_MR_Imaging_with_Partially_Known_Support
Assuming partially known support information, the authors of [28] also propose a modification to ℓ 1 -minimization similar to [39] and provide experimental results in the application of dynamic ...
https://www.osapublishing.org/oe/abstract.cfm?uri=oe-20-15-16510
Compressed sensing (CS) can recover sparse signals from under-sampled measurements. In this work, we have developed an advanced CS framework for photoacoustic computed tomography (PACT). During the reconstruction, a small part of the nonzero signals’ locations in the transformed sparse domain is used as partially known support (PKS). PACT reconstructions have been performed with under ...
https://www.sciencedirect.com/science/article/pii/S0165168410002276
This short note studies a variation of the compressed sensing paradigm introduced recently by Vaswani et al., i.e., the recovery of sparse signals from a certain number of linear measurements when the signal support is partially known.Cited by: 122
https://www.academia.edu/11098297/Iterative_algorithms_for_compressed_sensing_with_partially_known_support
Iterative algorithms for compressed sensing with partially known support
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