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» On the Scaling Law for Compressive Sensing and its Applicati...
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STOC
2007
ACM
106views Algorithms» more  STOC 2007»
14 years 5 months ago
One sketch for all: fast algorithms for compressed sensing
Compressed Sensing is a new paradigm for acquiring the compressible signals that arise in many applications. These signals can be approximated using an amount of information much ...
Anna C. Gilbert, Martin J. Strauss, Joel A. Tropp,...
ICASSP
2009
IEEE
13 years 11 months ago
Real-time dynamic MR image reconstruction using Kalman Filtered Compressed Sensing
In recent work, Kalman Filtered Compressed Sensing (KF-CS) was proposed to causally reconstruct time sequences of sparse signals, from a limited number of “incoherent” measure...
Chenlu Qiu, Wei Lu, Namrata Vaswani
ICASSP
2010
IEEE
13 years 4 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...
WMCSA
2008
IEEE
13 years 11 months ago
Urban sensing systems: opportunistic or participatory?
The development of sensing systems for urban deployments is still in its infancy. An interesting unresolved issue is the precise role assumed by people within such systems. This i...
Nicholas D. Lane, Shane B. Eisenman, Mirco Musoles...
VTC
2010
IEEE
195views Communications» more  VTC 2010»
13 years 2 months ago
Efficiency of Distributed Compression and Its Dependence on Sensor Node Deployments
Abstract--In this paper we analyze the energy-efficiency of distributed compression and its dependence on the node deployment strategies for Wireless Sensor Networks (WSNs). Reduce...
Frank Oldewurtel, Janne Riihijärvi, Petri M&a...