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ISBI
2009
IEEE
14 years 3 months ago
Performance Evaluation of Accelerated Functional MRI Acquisition Using Compressed Sensing
Functional MRI (fMRI) has been widely accepted as a standard tool to study the function of brain. However, because of the limited temporal resolution of MR scanning, researchers h...
Hong Jung, Jong Chul Ye
ICASSP
2008
IEEE
14 years 3 months ago
Approximate lower bounds for rate-distortion in compressive sensing systems
We attempt to quantify the possible gains that can be achieved by examining a rate-distortion competition between a conventional and a compressive sampling solution to data rate r...
Bernard Mulgrew, Michael E. Davies
ICIP
2009
IEEE
13 years 6 months ago
Randomness-in-Structured Ensembles for compressed sensing of images
Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...
Abdolreza A. Moghadam, Hayder Radha
ICASSP
2011
IEEE
13 years 9 days ago
Using the kernel trick in compressive sensing: Accurate signal recovery from fewer measurements
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
Hanchao Qi, Shannon Hughes
CORR
2008
Springer
197views Education» more  CORR 2008»
13 years 8 months ago
Sequential adaptive compressed sampling via Huffman codes
In this paper we introduce an information theoretic approach and use techniques from the theory of Huffman codes to construct a sequence of binary sampling vectors to determine a s...
Akram Aldroubi, Haichao Wang, Kourosh Zarringhalam