Dynamic sparse coding with smoothing proximal gradient method


In this work we focus on the problem of estimating time-varying sparse signals from a sequence of under-sampled observations. We formulate this problem as estimating hidden states in a dynamic model and exploit the underlying temporal structure to find a more accurate solution, particularly when the information in the observations is at scarce. We propose… (More)
DOI: 10.1109/ICASSP.2014.6854995


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