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TIT
2010
128views Education» more  TIT 2010»
12 years 11 months ago
Shannon-theoretic limits on noisy compressive sampling
In this paper, we study the number of measurements required to recover a sparse signal in M with L nonzero coefficients from compressed samples in the presence of noise. We conside...
Mehmet Akçakaya, Vahid Tarokh
CORR
2011
Springer
176views Education» more  CORR 2011»
12 years 11 months ago
Matched Filtering from Limited Frequency Samples
In this paper, we study a simple correlation-based strategy for estimating the unknown delay and amplitude of a signal based on a small number of noisy, randomly chosen frequency-...
Armin Eftekhari, Justin K. Romberg, Michael B. Wak...
CORR
2011
Springer
259views Education» more  CORR 2011»
12 years 11 months ago
The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range
Compressive sensing (CS) exploits the sparsity present in many common signals to reduce the number of measurements needed for digital acquisition. With this reduction would come, ...
Mark A. Davenport, Jason N. Laska, John R. Treichl...
CORR
2008
Springer
121views Education» more  CORR 2008»
13 years 4 months ago
Rate-Distortion via Markov Chain Monte Carlo
We propose an approach to lossy source coding, utilizing ideas from Gibbs sampling, simulated annealing, and Markov Chain Monte Carlo (MCMC). The idea is to sample a reconstructio...
Shirin Jalali, Tsachy Weissman