Dynamic Compressive Sensing of Time-Varying Signals Via Approximate Message Passing

@article{Ziniel2013DynamicCS,
  title={Dynamic Compressive Sensing of Time-Varying Signals Via Approximate Message Passing},
  author={Justin Ziniel and Philip Schniter},
  journal={IEEE Transactions on Signal Processing},
  year={2013},
  volume={61},
  pages={5270-5284}
}
In this work the dynamic compressive sensing (CS) problem of recovering sparse, correlated, time-varying signals from sub-Nyquist, non-adaptive, linear measurements is explored from a Bayesian perspective. While there has been a handful of previously proposed Bayesian dynamic CS algorithms in the literature, the ability to perform inference on high-dimensional problems in a computationally efficient manner remains elusive. In response, we propose a probabilistic dynamic CS signal model that… CONTINUE READING
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