Advanced Stochastic Signal Processing and Computational Methods: Theories and Applications
Description:
Compressed sensing has been proposed as a computationally efficient method to estimate the finite-dimensional signals. The idea is to develop an undersampling operator that can sample the large but finite-dimensional sparse signals with a rate much below the required Nyquist rate. In other words, considering the sparsity level of the signal, the compressed sensing samples the signal with a rate proportional to the amount of information hidden in the signal. In this dissertation, first, we emplo…
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Date:
August 2022
Creator:
Robaei, Mohammadreza