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» Compressed sensing with sequential observations
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TIP
2010
127views more  TIP 2010»
13 years 6 months ago
Bayesian Compressive Sensing Using Laplace Priors
In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
TIT
2010
174views Education» more  TIT 2010»
13 years 2 months ago
Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...
TSP
2010
13 years 2 months ago
LS-CS-residual (LS-CS): compressive sensing on least squares residual
We consider the problem of recursively and causally reconstructing time sequences of sparse signals (with unknown and time-varying sparsity patterns) from a limited number of noisy...
Namrata Vaswani
TIT
2011
157views more  TIT 2011»
13 years 2 months ago
Decentralized Sequential Hypothesis Testing Using Asynchronous Communication
—An asymptotically optimum test for the problem of decentralized sequential hypothesis testing is presented. The induced communication between sensors and fusion center is asynch...
Georgios Fellouris, George V. Moustakides
TSP
2010
13 years 2 months ago
Sparse channel estimation for multicarrier underwater acoustic communication: from subspace methods to compressed sensing
Abstract--In this paper, we investigate various channel estimators that exploit channel sparsity in the time and/or Doppler domain for a multicarrier underwater acoustic system. We...
Christian R. Berger, Shengli Zhou, James C. Preisi...