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ICASSP
2011
IEEE
13 years 9 days ago
Compressive power spectral density estimation
In this paper, we consider power spectral density estimation of bandlimited, wide-sense stationary signals from sub-Nyquist sampled data. This problem has recently received attent...
Michael A. Lexa, Mike E. Davies, John S. Thompson,...
NIPS
2008
13 years 10 months ago
Sparse Signal Recovery Using Markov Random Fields
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Ric...
ICASSP
2008
IEEE
14 years 3 months ago
A compressive beamforming method
Compressive Sensing (CS) is an emerging area which uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compres...
Ali Cafer Gurbuz, James H. McClellan, Volkan Cevhe...
ICASSP
2008
IEEE
14 years 3 months ago
Finding needles in noisy haystacks
The theory of compressed sensing shows that samples in the form of random projections are optimal for recovering sparse signals in high-dimensional spaces (i.e., finding needles ...
Rui M. Castro, Jarvis Haupt, Robert Nowak, Gil M. ...
INFOCOM
2010
IEEE
13 years 7 months ago
Queuing Analysis in Multichannel Cognitive Spectrum Access: A Large Deviation Approach
Abstract—The queueing performance of a (secondary) cognitive user is investigated for a hierarchical network where there are N independent and identical primary users. Each prima...
Amine Laourine, Shiyao Chen, Lang Tong