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ICASSP
2010
IEEE
15 years 6 months ago
Texas Hold 'Em algorithms for distributed compressive sensing
This paper develops a new class of algorithms for signal recovery in the distributed compressive sensing (DCS) framework. DCS exploits both intra-signal and inter-signal correlati...
Stephen R. Schnelle, Jason N. Laska, Chinmay Hegde...
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ICASSP
2010
IEEE
15 years 6 months ago
Multi-object filtering from image sequence without detection
Almost every single-view visual multi-target tracking method presented in the literature includes a detection routine that maps the image data to point measurements relevant to th...
Reza Hoseinnezhad, Ba-Ngu Vo, David Suter, Ba-Tuon...
CORR
2010
Springer
166views Education» more  CORR 2010»
15 years 6 months ago
The dynamics of message passing on dense graphs, with applications to compressed sensing
`Approximate message passing' algorithms proved to be extremely effective in reconstructing sparse signals from a small number of incoherent linear measurements. Extensive num...
Mohsen Bayati, Andrea Montanari
CORR
2008
Springer
118views Education» more  CORR 2008»
15 years 6 months ago
Quantifying Homology Classes
We develop a method for measuring homology classes. This involves three problems. First, we define the size of a homology class, using ideas from relative homology. Second, we defi...
Chao Chen, Daniel Freedman
CORR
2010
Springer
116views Education» more  CORR 2010»
15 years 6 months ago
Restricted Isometries for Partial Random Circulant Matrices
In the theory of compressed sensing, restricted isometry analysis has become a standard tool for studying how efficiently a measurement matrix acquires information about sparse an...
Holger Rauhut, Justin K. Romberg, Joel A. Tropp