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» Reconstructing sparse signals from their zero crossings
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IPMI
2007
Springer
14 years 7 months ago
Multi-fiber Reconstruction from Diffusion MRI Using Mixture of Wisharts and Sparse Deconvolution
Abstract. In this paper, we present a novel continuous mixture of diffusion tensors model for the diffusion-weighted MR signal attenuation. The relationship between the mixing dist...
Bing Jian, Baba C. Vemuri
CISS
2010
IEEE
12 years 10 months ago
Average case analysis of sparse recovery from combined fusion frame measurements
—Sparse representations have emerged as a powerful tool in signal and information processing, culminated by the success of new acquisition and processing techniques such as Compr...
Petros Boufounos, Gitta Kutyniok, Holger Rauhut
ICC
2008
IEEE
156views Communications» more  ICC 2008»
14 years 1 months ago
Cross-Layer Design for the MIMO System with Zero-Forcing Receiver in the Presence of Channel Estimation Error
—Multiple input multiple output (MIMO) system has been recognized as a promising candidate for future wireless communication. The adaptive modulation which adjusts the transmitte...
Feng Jiang, Ying Wang, Xi Fang, Kai Sun, Guona Hu,...
NIPS
2007
13 years 8 months ago
Compressed Regression
Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse...
Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
CORR
2008
Springer
129views Education» more  CORR 2008»
13 years 6 months ago
Hierarchical Bayesian sparse image reconstruction with application to MRFM
This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gau...
Nicolas Dobigeon, Alfred O. Hero, Jean-Yves Tourne...